Aging, Author Interviews, Lancet, Medical Imaging, Technology / 24.08.2023

MedicalResearch.com Interview with: [caption id="attachment_60799" align="alignleft" width="128"]Dr. Daiju UedaDepartment of Diagnostic and Interventional Radiology Graduate School of Medicine Osaka Metropolitan University Osaka, Japan Dr. Ueda[/caption] Dr. Daiju Ueda Department of Diagnostic and Interventional Radiology Graduate School of Medicine Osaka Metropolitan University Osaka, Japan MedicalResearch.com: What is the background for this study? Response:  We were inspired by the potential of chest radiography as a biomarker for aging. Previous research had utilized chest radiographs for age estimation, but these studies often involved cohorts with diseases.
Author Interviews, Health Care Systems, JAMA, Technology, UCSD / 01.05.2023

MedicalResearch.com Interview with: Zechariah Zhu, B.S. Affiliate Scientist with the Qualcomm Institute at UC San Diego and study co-author First author: John W. Ayers, PhD, MA MedicalResearch.com: What is the background for this study? Response: In today’s day and age (especially after the COVID-19 pandemic), an increasing number of people are turning to virtual options for healthcare. Most notably, there was a 1.6-fold increase in electronic patient messages, which significantly increased the burden on physicians, with a record-high proportion of physicians (62%) reporting burnout symptoms. On the other hand, we also see the rise of AI technologies like ChatGPT—an AI chatbot assistant that has taken the world by storm recently with its ability to provide lengthy response essays to many questions it is asked. Our objective for this study, then, was to evaluate the ability of ChatGPT to provide quality and empathetic responses to patient questions.
AHA Journals, Author Interviews, Heart Disease, Technology, Yale / 09.11.2022

MedicalResearch.com Interview with: [caption id="attachment_59724" align="alignleft" width="150"] Dr. Dhingra[/caption] Lovedeep Singh Dhingra, MBBS Postdoctoral Research Associate Cardiovascular Data Science (CarDS) Lab Yale School of Medicine MedicalResearch.com: What is the background for this study? What are the main findings? Response: Wearable devices are shown to have multiple health-related features, including heart rate and activity monitoring, ECG tracing, and blood pressure monitoring. In our analyses of the nationally-representative Health Information National Trends Survey (HINTS), we discovered that patients with and at risk of cardiovascular disease are less likely to use wearables. Older patients, patients with lower education, and patients with lower incomes are less likely to use wearables. Also, among adults with access to wearables, patients with cardiovascular disease use their devices less frequently as compared to the overall population.
Author Interviews, Brigham & Women's - Harvard, Cancer Research, JAMA, Lancet, Lung Cancer, Medical Imaging, Technology / 07.09.2022

MedicalResearch.com Interview with: [caption id="attachment_59510" align="alignleft" width="200"]Raymond H. Mak, MD Radiation Oncology Disease Center Leader for Thoracic Oncology Director of Patient Safety and QualityDirector of Clinical Innovation Associate Professor, Harvard Medical School Cancer - Radiation Oncology, Radiation Oncology Department of Radiation Oncology Brigham and Women's Hospital Dr. Mak[/caption] Raymond H. Mak, MD Radiation Oncology Disease Center Leader for Thoracic Oncology Director of Patient Safety and QualityDirector of Clinical Innovation Associate Professor, Harvard Medical School Cancer - Radiation Oncology, Radiation Oncology Department of Radiation Oncology Brigham and Women's Hospital MedicalResearch.com: What is the background for this study? What is the algorithm detecting? Response: Lung cancer, the most common cancer worldwide is highly lethal, but can be treated and cured in some cases with radiation therapy.  Nearly half of lung cancer patients will eventually require some form of radiation therapy, but the planning for a course of radiation therapy currently entails manual, time-consuming, and resource-intensive work by highly trained physicians to segment (target) the cancerous tumors in the lungs and adjacent lymph nodes on three-dimensional images (CT scans). Prior studies have shown substantial variation in how expert clinicians delineate these targets, which can negatively impact outcomes and there is a projected shortage of skilled medical staff to perform these tasks worldwide as cancer rates increase. To address this critical gap, our team developed deep learning algorithms that can automatically target lung cancer in the lungs and adjacent lymph nodes from CT scans that are used for radiation therapy planning, and can be deployed in seconds. We trained these artificial intelligence (AI) algorithms using expert-segmented targets from over 700 cases and validated the performance in over 1300 patients in external datasets (including publicly available data from a national trial), benchmarked its performance against expert clinicians, and then further validated the clinical usefulness of the algorithm in human-AI collaboration experiments that measured accuracy, task speed, and end-user satisfaction.
Heart Disease, Technology / 19.04.2022

[caption id="attachment_59059" align="alignleft" width="150"]Ken Londoner Mr. Londoner[/caption] Ken Londoner, MBA Founder, Chief Executive Officer, Chairman, and Director BioSig Technologies MedicalResearch.com: Would you briefly describe the condition of Atrial fibrillation (AFib)? Whom does AFib primarily affect and how common is it?  What are the potential complication of AFib?  Response: Atrial Fibrillation, or Afib—the most common heart rhythm disturbance—affects over 33 million people across the globe. Afib is caused by faulty electrical signals in the upper chambers of the heart (the atria) that cause it to beat too fast or irregularly—often more than 400 beats per minute.*  The condition can lead to serious health consequences, including stroke, blood clots, or sudden cardiac arrest. Stroke is among the most serious health concerns for Afib patients, with research suggesting a Afib carries a 5-fold increased risk of stroke— especially when Afib is left untreated. With a lifetime risk of more than 20 percent*, Afib can affect anyone. However, the condition is most common in those 65 years and older.  Individuals with underlying health complications, including heart disease, high blood pressure, thyroid problems, or excessive alcohol use are also at a greater risk of developing Afib.*
Author Interviews, Ophthalmology, Technology / 01.04.2022

MedicalResearch.com Interview with: Scott D. Barnes, MD Chief Medical Officer STAAR Surgical https://staar.com/MedicalResearch.com:  What is the background for the EVO procedure?  Would you briefly describe what is meant by myopia and how common it is? Response: EVO is a clinically-proven implantable lens that corrects common vision problems such as nearsightedness and nearsightedness with astigmatism. EVO can be the solution for people who want to get rid of their glasses or contact lenses. Myopia (or nearsightedness) is the most common ocular disorder worldwide and its incidence is increasing significantly. An estimated 30% of the world's population, or 2.6 billion people, have myopia and this number is projected to rise to 50% of the global population by the year 2050.
Author Interviews, Education, JAMA, Surgical Research, Technology / 22.03.2022

MedicalResearch.com Interview with: [caption id="attachment_58936" align="alignleft" width="125"]Ali M. Fazlollahi, MSc ,McGill Medicine, Class of 2025 Neurosurgical Simulation and Artificial Intelligence Learning Centre Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital Faculty of Medicine and Health Sciences McGill University, Montreal, Canada Ali M. Fazlollahi[/caption] Ali M. Fazlollahi, MSc, McGill Medicine Class of 2025 Neurosurgical Simulation and Artificial Intelligence Learning Centre Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital Faculty of Medicine and Health Sciences McGill University, Montreal, Canada MedicalResearch.com:  What is the background for this study?  Response: COVID-19 disrupted hands on surgical exposure of medical students and academic centres around the world had to quickly adapt to teaching technical skills remotely. At the same time, advances in artificial intelligence (AI) allowed researchers at the Neurosurgical Simulation and Artificial Intelligence Learning Centre to develop an intelligent tutoring system that evaluates performance and provides high-quality personalized feedback to students. Because this is the first AI system capable of providing surgical instructions in simulation, we sought to evaluate its effectiveness compared with learning from expert human instructors who provided coaching remotely.
Author Interviews, Genetic Research, Heart Disease, Technology / 17.03.2022

MedicalResearch.com Interview with: [caption id="attachment_58888" align="alignleft" width="200"]Ali Torkamani, Ph.D. Director of Genomics and Genome Informatics Scripps Research Translational Institute Professor, Integrative Structural and Computational Biology Scripps Research La Jolla, CA 92037 Dr. Torkamani[/caption] Ali Torkamani, Ph.D. Director of Genomics and Genome Informatics Scripps Research Translational Institute Professor, Integrative Structural and Computational Biology Scripps Research La Jolla, CA 92037 MedicalResearch.com:  What is the background for this study?  Response: Prior research has shown that people with higher polygenic risk for coronary artery disease achieve greater risk reduction with statin or other lipid lowering therapy. In general, adherence to standard guidelines for lipid lowering therapy is low - about 30% of people who should be on lipid lowering therapy are, with no correlation to their genetic risk. We set out to see whether communicating personalized risk, including polygenic risk, for coronary artery disease would drive the adoption of lipid lowering therapy.
Author Interviews, COVID -19 Coronavirus, Technology / 03.02.2022

MedicalResearch.com Interview with: [caption id="attachment_58711" align="alignleft" width="150"]Michael J. Mahan Ph.D Professor Dept of Molecular, Cellular, and Developmental Biology University of California, Santa Barbara, CA 93106-9625 Dr. Mahan[/caption] Michael J. Mahan Ph.D Professor Dept of Molecular, Cellular, and Developmental Biology University of California, Santa Barbara, CA 93106-9625 MedicalResearch.com:  What is the background for this study?  Response: A critical need exists in resource-poor settings for low-cost, low-tech, yet highly reliable and scalable testing for SARS-CoV-2 virus that is robust against circulating variants. 
Author Interviews, Diabetes, NEJM, Pediatrics, Technology / 20.01.2022

MedicalResearch.com Interview with: [caption id="attachment_58667" align="alignleft" width="200"]Dr Julia Ware (née Fuchs) Clinical Research Associate Wellcome-MRC Institute of Metabolic Science-Metabolic Research Laboratories  and Medical Research Council Metabolic Diseases Unit, University of Cambridge Addenbrooke’s Hospital, Cambridge  Dr. Ware[/caption] Dr Julia Ware (née Fuchs) Clinical Research Associate Wellcome-MRC Institute of Metabolic Science-Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, University of Cambridge Addenbrooke’s Hospital, Cambridge MedicalResearch.com: What is the background for this study? Response: Management of type 1 diabetes is challenging in very young children, due to their high variability of insulin requirements and unpredictable eating and activity patterns. As a result, many young children do not meet the recommended glycemic targets, or only maintain recommended glycemic control with extensive caregiver input. This in turn leads to high management burden and reduced quality of life for the whole family. While the increasing use of continuous glucose-monitoring devices and insulin-pump therapy has led to reductions in the incidence of severe hypoglycaemia and diabetic ketoacidosis, and has been accompanied by modest improvements in glycemic control, the burden of management has remained high. Hybrid closed-loop systems (also called an artificial pancreas), in which an algorithm automatically adjusts insulin delivery on the basis of real-time sensor glucose levels, may address ongoing challenges in this age group. However, to date hybrid closed-loop studies involving very young children have been small and of short duration and the efficacy and safety of longer term use of a closed-loop system, as compared with standard therapy, was unclear.   To address this knowledge gap, we compared 16-week use of the Cambridge closed-loop algorithm with sensor-augmented pump therapy in children aged 1 to 7 years with type 1 diabetes in a multi-national randomised crossover study.
Author Interviews, COVID -19 Coronavirus, Environmental Risks, Technology / 13.01.2022

MedicalResearch.com Interview with: [caption id="attachment_58643" align="alignleft" width="150"]Krystal Pollitt, PhD, P.Eng. Dr. Pollitt[/caption] Krystal Pollitt, PhD, P.Eng. Assistant Professor of Epidemiology (Environmental Health Sciences) Assistant Professor in Chemical and Environmental Engineering Affiliated Faculty, Yale Institute for Global Health Yale School of Public Health  MedicalResearch.com: What is the background for this study? Response: People infected with COVID-19 can release SARS-CoV-2 virus in aerosol and droplets when they exhale. This can be from coughing or sneezing but also when they speaker or just breathe. While the larger droplets can settle to the ground quickly (seconds to minutes), smaller aerosol can remain in the air in longer periods (minutes to hours). SARS-CoV-2 can be transmitted by inhaling aerosol or droplets containing infectious virus. The Fresh Air Clip enables detection of droplet and aerosol containing virus.
Author Interviews, Cancer Research, Dermatology, Lancet, Melanoma, Technology / 11.11.2021

MedicalResearch.com Interview with: [caption id="attachment_58371" align="alignleft" width="150"]Dr David Wen BM BCh NIHR Academic Clinical Fellow in Dermatology University of Oxford Dr. Wen[/caption] Dr David Wen BM BCh NIHR Academic Clinical Fellow in Dermatology University of Oxford MedicalResearch.com: What is the background for this study? Response: Publicly available skin image datasets are commonly used to develop machine learning (ML) algorithms for skin cancer diagnosis. These datasets are often utilised as they circumvent many of the barriers associated with large scale skin lesion image acquisition. Furthermore, publicly available datasets can be used as a benchmark for direct comparison of algorithm performance. Dataset and image metadata provide information about the disease and population upon which the algorithm was trained or validated on. This is important to know because machine learning algorithms heavily depend on the data used to train them; algorithms used for skin lesion classification frequently underperform when tested on independent datasets to which they were trained on. Detailing dataset composition is essential for extrapolating assumptions of generalisability of algorithm performance to other populations. At the time this review was conducted, the total number of publicly available datasets globally and their respective content had not previously been characterised. Therefore, we aimed to identify publicly available skin image datasets used to develop ML algorithms for skin cancer diagnosis, to categorise their data access requirements, and to systematically evaluate their characteristics including associated metadata.  
Surgical Research, Technology / 14.10.2021

Medicine is ever evolving, but it might surprise you to hear how far we’ve come even since the turn of the century. Advancements in technology have allowed for some amazing upgrades in medicine that could only be imagined in sci-fi movies before, and new developments in drugs have vastly increased the average life expectancy, from 77.74 in 2000 to a high of 81.3 in 2014. Read on to find out more about our top picks for the most influential advancements in medicine. Information technology An often overlooked but greatly impactful aspect of medicine, information technology has allowed for the smooth and faster running of hospitals. Like every other aspect of life, technology has infiltrated hospitals and GPs at a basic and far-reaching level, allowing for safer and more secure running of hospitals as well as aiding diagnosis earlier and minimally invasive procedures to create less pain and quicker healing. Rather than sifting through filing rooms for that one patient, staff can access a patient’s file on cloud storage, where it is free from other prying eyes. Remote consultations allow for neither patient or doctor to travel to do a consultation, and an encyclopedia of symptoms and treatments are available at doctors’ fingertips. Technology has taken the routine and tedious aspects of patient care out of the equation, or at least streamlined it, so that doctors can focus on their patients. Filing, record maintenance and other routine tasks, are all done quickly with the help of apps and cloud storage. Streamlining processes like no exam life insurance allows for doctors to focus on the care of their patients while you offer other evidence like family history and pre-existing conditions. Doctors are working faster, patients get seen quicker, their prescriptions are issued sooner.
Technology / 08.10.2021

Three way hospitals have changedThe evolution of hospitals is truly something to marvel at. Modern-day hospitals perform ground-breaking procedures, unearth new and improved ways of caring for patients, and constantly evolve thanks to regular inspections. Hospitals have had to advance because of the ever-growing demands of the public - and the Guardian reported there are still 5.6 million people waiting for treatment. With so many people waiting, how are hospitals coping with the increased demand? They're evolving - and here's how.
Author Interviews, Biomarkers, Heart Disease, JAMA, Technology / 05.10.2021

MedicalResearch.com Interview with: [caption id="attachment_58206" align="alignleft" width="200"]Pinar Zorlutuna, PhD Sheehan Family Collegiate Professor of Engineering Aerospace and Mechanical Engineering  Chemical and Biomolecular Engineering (Concurrent) Bioengineering Graduate Program  University of Notre Dame Dr. Zorlutuna[/caption] Pinar Zorlutuna, PhD Sheehan Family Collegiate Professor of Engineering Aerospace and Mechanical Engineering Chemical and Biomolecular Engineering (Concurrent) Bioengineering Graduate Program University of Notre Dame  MedicalResearch.com: What is the background for this study? Response: Acute myocardial infarction (AMI) is the primary cause of death among cardiovascular diseases. The current clinical standard of diagnosis combines echocardiogram (ECG) and several circulating protein biomarkers from plasma. In their current state, both are incapable of distinguishing between patients with and without complete coronary occlusion, unless additional invasive testing is implemented, and both have significant false positive rates. MicroRNAs (miRNAs) have shown great potential as rapid and discriminating biomarkers for acute myocardial infarction (AMI) diagnosis.
Author Interviews, Education, Medical Imaging, Technology / 13.08.2021

MedicalResearch.com Interview with: Ryan C. Gibbons, MD, FAAEM, FACEP Associate Professor of Emergency Medicine Director of the Emergency Ultrasound Fellowship Associate Director of the Division of Emergency Ultrasound Department of Emergency Medicine Director of Ultrasound in Medical Education Lewis Katz School of Medicine at Temple University MedicalResearch.com: What is the background for this study?  How was the gift funded? Butterfly needle visualizatioResponse: Point-of-care ultrasound is one of the most significant advances in bedside patient care, and its use is expanding across nearly all fields of medicine. In order to best prepare medical students for residency and beyond, it is imperative to begin POCUS training as early as possible. At the Lewis Katz School of Medicine at Temple University, we introduced POCUS education over a decade ago and have expanded it since then. By providing each student with a Butterfly iQ device, we can augment our curriculum significantly. In addition to our robust pre-clinical sessions, now we will expand into the clinical years highlighting the utility of POCUS with actual patients. This gift was made possible by the incredible generosity of Dr. Ronald Salvitti, MD ’63. 
Author Interviews, COVID -19 Coronavirus, Sleep Disorders, Technology / 03.06.2021

MedicalResearch.com Interview with: [caption id="attachment_57551" align="alignleft" width="203"]Michele Ferrara, PhD. Professor of Psychobiology and Physiological Psychology Chair of the Psychology Didactic Council Department of Biotechnological and Applied Clinical Sciences University of L'Aquila Dr. Ferrara[/caption] Michele Ferrara, PhD. Professor of Psychobiology and Physiological Psychology Chair of the Psychology Didactic Council Department of Biotechnological and Applied Clinical Sciences University of L'Aquila MedicalResearch.com: What is the background for this study? Response: During the current period of social distancing, the pervasive increase in the use of electronic devices (smartphones, computers, tablets and televisions) is an indisputable fact. Especially during the long lockdown period of Spring 2020, technologies played a pivotal role in coping with the unprecedented and stressful isolation phase. However, exposure to backlit screens in the hours before falling asleep can have serious repercussions on sleep health: on the one hand, by mimicking the effects of exposure to sunlight, and thus interfering with the circadian rhythm of the hormone melatonin, and on the other hand, counteracting the evening sleepiness due to the emotionally and psycho-physiologically activating contents. In light of this assumption, we decided to test longitudinally during the third and the seventh week of lockdown a large Italian sample (2123 subjects) through a web-based survey. We assessed sleep disturbances/habits and the occurring changes of electronic device usage in the 2 hours before the sleep onset.
Author Interviews, Technology / 28.05.2021

MedicalResearch.com Interview with: [caption id="attachment_57497" align="alignleft" width="150"]Dani Clode Designer & Senior Research Technician Plasticity Laboratory Institute of Cognitive Neuroscience University College London Dani Clode[/caption] Dani Clode Designer & Senior Research Technician Plasticity Laboratory Institute of Cognitive Neuroscience University College London   MedicalResearch.com: What was the inspiration behind creating the Third Thumb? [caption id="attachment_57498" align="alignleft" width="145"]Third Thumb Dani Clode Design Third Thumb Dani Clode Design[/caption] Response: From a design perspective, augmentation is about designing a new relationship with technology, creating something that is no longer just a tool for the hand, but instead an extension of the hand. I created the Third Thumb during my Design Product Masters project at the Royal College of Art (London). The Third Thumb is a flexible 3D-printed thumb extension for your hand, controlled by your toes. It is operated wirelessly with pressure sensors and affords proportional control over two degrees of freedom. The project began as a way to better understand what it was like to control something extra attached to my body. As an upper-limb prosthetics designer, I wanted to understand the unique relationship between a person and a prosthetic, it’s a relationship unlike any other product, and I wanted to explore that. The Plasticity Lab then got in contact with me after seeing the Third Thumb online, as they were already exploring augmentation in the brain. We started collaborating on this research shortly after, and I now work as an in-house designer for the Plasticity Lab, collaborating on neuroscience research.
Author Interviews, Cancer Research, COVID -19 Coronavirus, Technology / 05.05.2021

MedicalResearch.com Interview with: [caption id="attachment_57335" align="alignleft" width="150"]Saket Navlakha PhD Simons Center for Quantitative Biology Cold Spring Harbor Laboratory Cold Spring Harbor, NY Dr. Navlakha[/caption] Saket Navlakha PhD Simons Center for Quantitative Biology Cold Spring Harbor Laboratory Cold Spring Harbor, NY  MedicalResearch.com: What is the background for this algorithm? How does it aide in patient care? Response: The machine learning algorithm helps to predict if and when a patient will develop severe COVID symptoms, based on information on how the patient presents on the day of infection. This could lead to improved patient outcomes, by getting a “heads up” on what may happen in the near future.
Author Interviews, COVID -19 Coronavirus, Technology / 04.05.2021

MedicalResearch.com Interview with: [caption id="attachment_57310" align="alignleft" width="200"]Dr. Peruvemba Dr. Peruvemba[/caption] Ramani “Ram” Peruvemba, MD, FASA Co-founder and CMO of HSR.health MedicalResearch.com: Would you tell us about your background?  Response: I am a dual-board certified Anesthesiologist and Pain Management physician, currently serving as the co-founder and CMO of HSR.health. I am a Health IT expert and well-versed in the clinical, regulatory, and policy issues surrounding healthcare. I leverage my expertise, professional networks, and insights to HSR.health to bring health risk information to industry. As a clinician, I formerly served as Vice Chairman of the board for the largest anesthesia provider in Maryland and led them through a private equity transaction that helped elevate our group onto a national platform. I have also served on the advisory boards of QSSI corp, a Health IT firm involved in the construction of Healthcare.gov and ultimately sold to Optum, as well as Welldoc, a digital health leader that developed the only FDA approved digital health solution for the management of diabetes. Through my role on the Maryland Health Services Cost Review Commissions Advisory Council, I play a key role in the development and implementation of the unique value based hospital payment system, the Total Cost of Care Model, in conjunction with CMS and CMMI. I currently serve on the board of the Maryland State Medical Society, MedChi, as chairman of the medical policy council, and am the President of the Maryland Society of Anesthesiologists. Most recently, I’m proud to share that I was named a 2021 Top 100 Healthcare Innovator for my leadership in HSR.health's efforts supporting COVID-19 pandemic response globally.
Author Interviews, Dermatology, JAMA, Technology / 28.04.2021

MedicalResearch.com Interview with: [caption id="attachment_57270" align="alignleft" width="176"]Yun Liu, PhD Google Health Palo Alto, California Dr. Yun Liu[/caption] Yun Liu, PhD Google Health Palo Alto, California MedicalResearch.com: What is the background for this study? Would you describe the system?  Does it use dermatoscopic images? Response: Dermatologic conditions are extremely common and a leading cause of morbidity worldwide. Due to limited access to dermatologists, patients often first seek help from non-specialists. However, non-specialists have been reported to have lower diagnostic accuracies compared to dermatologists, which may impact the quality of care. In this study, we built upon prior work published in Nature Medicine, where we developed a computer algorithm (a deep learning system, DLS) to interpret de-identified clinical images of skin conditions and associated medical history (such as whether the patient reported a history of psoriasis). These clinical images are taken using consumer-grade hardware such as point-and-shoot cameras and tablets, which we felt was a more accessible and widely-available device compared to dermatoscopes. Given such images of the skin condition as input, the DLS outputs a differential diagnosis, which is a rank-ordered list of potential matching skin conditions. In this paper, we worked with user experience researchers to create an artificial intelligence (AI) tool based on this DLS. The tool was designed to provide clinicians with additional information per skin condition prediction, such as textual descriptions, similar-appearing conditions, and the typical clinical workup for the condition. We then conducted a randomized study where 40 clinicians (20 primary care physicians, 20 nurse practitioners) reviewed over 1,000 cases -- with half the cases with the AI-based assistive tool, and half the cases without. For each case, the reference diagnosis was based on a panel of 3 dermatologists. 
Author Interviews, Brigham & Women's - Harvard, Cost of Health Care, COVID -19 Coronavirus, Electronic Records, JAMA, Technology / 04.03.2021

MedicalResearch.com Interview with: [caption id="attachment_56821" align="alignleft" width="107"]Carlo Giovanni Traverso, MB, BChir, PhD Dr. Traverso[/caption] Carlo Giovanni Traverso, MB, BChir, PhD Associate Physician, Brigham and Women's Hospital Assistant Professor, [caption id="attachment_56823" align="alignleft" width="150"]Peter R. Chai, MD, MMS Emergency Medicine Physician and Medical Toxicologist Dr. Chai[/caption] Peter R. Chai, MD, MMS Emergency Medicine Physician and Medical Toxicologist Harvard Medical School Brigham and Women's Hospital Department of Medicine   Dr-Spot-HealthCare-Assistant.jpgMedicalResearch.com: What is the background for this study? What are some of the functions that Dr. Spot can facilitate? Response: During the COVID-19 pandemic, we wanted to consider innovative methods to provide additional social distance for physicians evaluating low acuity individuals who may have COVID-19 disease in the emergency department. While other health systems had instituted processes like evaluating patients from outside of emergency department rooms or calling patients to obtain a history, we considered the use of a mobile robotic system in collaboration with Boston Dynamics to provide telemedicine triage on an agile platform that could be navigated around a busy emergency department. Dr. Spot was built with a camera system to help an operator navigate it through an emergency department into a patient room where an on-board tablet would permit face-to-face triage and assessment of individuals.
Author Interviews, Leukemia, Stem Cells, Technology / 11.02.2021

MedicalResearch.com Interview with: [caption id="attachment_56645" align="alignleft" width="130"]Eirini Papapetrou, MD, PhD Associate Professor Department of Oncological Sciences Icahn School of Medicine at Mount Sinai New York, NY 10029 Dr. Papapetrou[/caption] Eirini Papapetrou, MD, PhD Associate Professor Department of Oncological Sciences Icahn School of Medicine at Mount Sinai New York, NY 10029 MedicalResearch.com: What is the background for this study? Would you tell us a little about acute myeloid leukemia? Response: Acute myeloid leukemia is a form of cancer of the blood. It is typically very aggressive and lethal without treatment. The main treatment is high-dose chemotherapy and it has not changed very much in decades. Some more recent "targeted" therapies that are less toxic help somewhat but still do not result in cures. We believe a reason for this might be that both chemotherapy and newer "targeted" therapies target the cells at the later stages of the disease and spare the earlier ones, which can then give rise to disease resistance and relapse. 
Author Interviews, COVID -19 Coronavirus, JAMA, Race/Ethnic Diversity, Social Issues, Technology, University of Pennsylvania / 30.12.2020

MedicalResearch.com Interview with: Srinath Adusumalli, MD, MSc, FACC Assistant Professor of Clinical Medicine Division of Cardiovascular Medicine| Penn Medicine Lauren A. Eberly, MD, MPH Division of Cardiovascular Medicine, Department of Medicine Hospital of the University of Pennsylvania, Philadelphia MedicalResearch.com: What is the background for this study?   Response: The coronavirus disease 2019 (COVID-19) pandemic has uprooted conventional health care delivery for routine ambulatory care, requiring health systems to rapidly adopt telemedicine capabilities. At Penn Medicine, we wanted to ensure that as we developed a new system of telemedical care, we were reaching all of the patients we serve and access to care was maintained. As such, we undertook this study to examine utilization of care as we continued to iterate on and develop our telemedical system of care.
Author Interviews, Cancer Research, JAMA, Prostate Cancer, Technology / 13.11.2020

MedicalResearch.com Interview with: [caption id="attachment_55940" align="alignleft" width="200"]Dave Steiner MD PhD Clinical Research Scientist Google Health, Palo Alto, California Dr. Steiner[/caption] Dave Steiner MD PhD Clinical Research Scientist Google Health, Palo Alto, California MedicalResearch.com: What is the background for this study? Response: For prostate cancer patients, the grading of cancer in prostate biopsies by pathologists is central to risk stratification and treatment decisions. However, the grading process can be subjective, often resulting in variability among pathologists. This variability can complicate diagnostic and treatment decisions. As an initial step towards addressing this problem, we and others in the field have recently developed artificial intelligence (AI) algorithms that perform on-par with expert pathologists for prostate cancer grading. Such algorithms have the potential to improve the quality and efficiency of prostate biopsy grading, but the impact of these algorithms when used by pathologists has not been well studied. In the current study, we developed and evaluated an AI-based assistant tool for use by pathologists while reviewing prostate biopsies.
Author Interviews, Fertility, Genetic Research, OBGYNE, Technology / 29.10.2020

MedicalResearch.com Interview with: PGT-A & ARTIFICIAL INTELLIGENCE IMPROVES PREGNANCY OUTCOMES FOR PATIENTS UNDERGOING IVF MedicalResearch.com Interview with: Michael Large, PhD Senior Director, Research at CooperGenomics CooperSurgical MedicalResearch.com: What is the background for this study? What are the main findings? Dr. Large: Independent study results, presented at the recent the American Society of Reproductive Medicine (ASRM) Virtual Scientific Congress, demonstrated a 13 percent relative increase in ongoing pregnancy and live birth rates associated with the use of CooperSurgical’s PGTaiSM 2.0 technology to screen embryos for in vitro fertilization (IVF). The single-center study was conducted by NYU Langone Fertility Center (NYULFC), part of The Prelude Network. Preimplantation Genetic Testing for aneuploidy (PGT-A) is performed on embryos produced through IVF; it provides genetic information to help identify embryos that are more likely to result in a successful pregnancy. PGTai 2.0 technology is an advancement in PGT-A testing platform that utilizes artificial intelligence to increase objectivity of this screening process. The study compared results from three next generation sequencing (NGS) genetic tests: Standard NGS, NGS with first generation artificial intelligence (PGTai 1.0 Technology Platform) and NGS with second generation artificial intelligence (PGTai 2.0 Technology Platform). The ongoing pregnancy and live birth rates significantly increased by a relative 13 percent in the PGTai 2.0 group as compared to subjective and prior methodologies. Study results also suggest that the increase in ongoing pregnancy and live births may be linked to improvements in several preceding IVF outcomes (implantation rates, clinical pregnancy rates and pregnancy loss.) MedicalResearch.com: What should readers take away from your report? Dr. Large: This research moves us an important step closer to our goal of increased live births, improved pregnancy outcomes and further reduction of multiples in pregnancy through greater confidence in single embryo transfer. An estimated 48.5 million couples – approximately 15% of couples -- are affected by infertility worldwide. 80,000 babies were born with IVF in 2017 in the United States and more than one million babies were born in the period 1987 to 2015 in the United States as a result of IVF. MedicalResearch.com: What recommendations do you have for future research this study? Dr. Large: The goal of PGT-A is to decrease risk and maximize the chances of IFV success by screening for embryos with the highest potential. This was precisely what NYULFC have observed so far with PGTai 2.0 compared to older technologies. To fully appreciate the impact that these improvements are having for patients, we’re excited to hear from additional IVF centers across the world as they utilize this technology. MedicalResearch.com: Is there anything else you would like to add? Any disclosures? Dr. Large: The study demonstrates CooperSurgical’s commitment to developing the most advanced technology in the field of genetic testing to advance reproductive medicine and help families. By applying artificial intelligence in the PGTaism2.0 technology, we leverage mathematical algorithms derived from real-world data to achieve objective embryo assessment. I am the Senior Director of Genomics Research and Development at CooperSurgical. Michael Large, PhD, is the Senior Director, Genomics Research and Development at CooperSurgical. His team recently led and continues to develop state-of-the-art analytical methods for interrogating Reproductive Genetics. Dr. Large earned his PhD in Cell and Molecular Biology from the Baylor College of Medicine and his Bachelor of Science in Cell and Molecular Biology from the University of Wisconsin – La Crosse. Michael Large, PhD Senior Director, Research at CooperGenomics CooperSurgical   MedicalResearch.com: What is the background for this study? What are the main findings? Dr. Large: Independent study results, presented at the recent the American Society of Reproductive Medicine (ASRM) Virtual Scientific Congress, demonstrated a 13 percent relative increase in ongoing pregnancy and live birth rates associated with the use of CooperSurgical’s PGTaiSM 2.0 technology to screen embryos for in vitro fertilization (IVF).[1] The single-center study was conducted by NYU Langone Fertility Center (NYULFC), part of The Prelude Network. Preimplantation Genetic Testing for aneuploidy (PGT-A) is performed on embryos produced through IVF; it provides genetic information to help identify embryos that are more likely to result in a successful pregnancy. PGTai 2.0 technology is an advancement in PGT-A testing platform that utilizes artificial intelligence to increase objectivity of this screening process. The study compared results from three next generation sequencing (NGS) genetic tests: Standard NGS, NGS with first generation artificial intelligence (PGTai 1.0 Technology Platform) and NGS with second generation artificial intelligence (PGTai 2.0 Technology Platform). The ongoing pregnancy and live birth rates significantly increased by a relative 13 percent in the PGTai 2.0 group as compared to subjective and prior methodologies. Study results also suggest that the increase in ongoing pregnancy and live births may be linked to improvements in several preceding IVF outcomes (implantation rates, clinical pregnancy rates and pregnancy loss.)
Author Interviews, COVID -19 Coronavirus, Health Care Systems, JAMA, Technology / 27.10.2020

MedicalResearch.com Interview with: [caption id="attachment_55764" align="alignleft" width="129"]Shira H. Fischer, MD, PhD RAND Corporation Boston, Massachusetts Dr. Fischer[/caption] Shira H. Fischer, MD, PhD RAND Corporation Boston, Massachusetts MedicalResearch.com: What is the background for this study? What are the main findings? Response: Before the COVID-19 outbreak, telehealth was talked about a lot, but it wasn’t widely available and wasn’t used that often. We wanted to know who was using telehealth, what the barriers to use were, and whether people would be willing to do so if it were available to them. We conducted a survey of over 2,500 Americans across the country and asked them about these topics. 
Author Interviews, Nutrition, NYU/NYMC, Pediatrics, Pediatrics, Technology / 26.10.2020

MedicalResearch.com Interview with: [caption id="attachment_55746" align="alignleft" width="200"]Marie Bragg, PhD Assistant Professor, Department of Population Health on Health Choice NYU College of Global Public Health Dr. Bragg[/caption] Marie Bragg, PhD Assistant Professor, Department of Population Health on Health Choice NYU College of Global Public Health MedicalResearch.com: What is the background for this study? Response: We know from previous research that children who see food advertisements eat significantly more calories than children who see non-food advertisements. Those studies led the World Health Organization and National Academy of Medicine to issue reports declaring that exposure to food advertising is a major driver of childhood obesity. What we don’t know is how frequently unhealthy food and beverage brands are appearing in YouTube videos posted by Kid Influencers. Kid influences are children whose parents film videos of the child playing with toys, unwrapping presents, eating food, or engaging in other family-friendly activities. The parents then post the videos to YouTube for other children and parents to view for entertainment. 
Author Interviews, Emergency Care, Social Issues, Technology / 23.10.2020

MedicalResearch.com Interview with: [caption id="attachment_55726" align="alignleft" width="133"]Susan Lu PhD Gerald Lyles Rising Star Associate Professor of Management Krannert School of Management Purdue University Dr. Love you to the moon and back![/caption] Susan Lu PhD Gerald Lyles Rising Star Associate Professor of Management Krannert School of Management Purdue University  MedicalResearch.com: What is the background for this study? Response: We started this project in 2016. Overcrowding in emergency rooms (ERs) is a common yet nagging problem. It not only is costly for hospitals but also compromises care quality and patient experience. Hence, finding effective ways to improve ER care delivery is of great importance. Meanwhile, the advancement of healthcare technologies including electronic medical records, online doctor ratings and 4G mobile network motivates us to think about the impact of telemedicine on ER operations in the near future. 
Thank you for visiting MedicalResearch.com Senior Editor, Marie Benz MD. For more information please email: info@MedicalResearch.com

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