Author Interviews, Nature, Technology, University of Pittsburgh / 26.02.2024

MedicalResearch.com Interview with: [caption id="attachment_61350" align="alignleft" width="150"]Jishnu Das, Ph.D.Center for Systems Immunology Departments of Immunology and Computational & Systems Biology, Assistant Professor School of Medicine University of Pittsburgh Dr. Das[/caption] Jishnu Das, Ph.D. Center for Systems Immunology Departments of Immunology and Computational & Systems Biology, Assistant Professor School of Medicine University of Pittsburgh MedicalResearch.com:  What is the background for this study? How does this new AI model work?  How is it different from other models? Response: Modern multi-omic technologies generate an enormous amount of data across scales of organization, and with differing resolution. While recent machine learning methods have harnessed these to predict clinical/physiological outcomes, they are often black boxes that do not provide meaningful inference beyond prediction. Differences in data generation modalities, redundancy in the data, as well as large numbers of irrelevant features make inference of biological mechanisms from high-dimensional omic datasets challenging. To address these challenges, we developed a machine learning technique called SLIDE (Significant Latent Factor Interaction Discovery and Exploration). We reasoned that features that are directly measured by current technologies are constrained by strengths and weaknesses of current platforms. So, while some observed features may be excellent correlates of outcomes of interest, inferring biological mechanisms from these multi-omic datasets requires us to delve beyond the observable into the hidden states, i.e., latent factors. These hidden states encapsulate the true drivers of underlying biological processes and capture a complex multi-scale interplay between entities measured by these datasets. Our method moves beyond simple biomarkers/correlates (“the what”) to hidden states that actually explain clinical/physiological outcomes (“the how” and “the why”).
Author Interviews, Autism, JAMA, Pediatrics, Technology / 08.01.2024

MedicalResearch.com Interview with: Karen F. Heffler, MD Researcher, Autism Spectrum Disorder Associate Professor, Department of Psychiatry Drexel University College of Medicine Philadelphia, PA MedicalResearch.com: What is the background for this study? children-watching-tv-pexels-photo-4740522 Response: Atypical sensory processing is common in neurodevelopmental disorders, affecting approximately 60% of children with ADHD and up to 90% of children with autism. Sensory symptoms are associated with hyperactivity, restricted/repetitive behavior, irritability, behavioral problems, and emotional dysregulation. Sensory-related meltdowns and symptoms can be very disruptive to family-life, interfere with family participation in community events and are associated with increased caregiver stress. Prior to this study there was little understanding of potential risk factors for atypical sensory processing. The researchers used data from the National Children’s Study to determine the association between early-life screen time and sensory processing outcomes among toddlers.
Technology / 27.12.2023

 Imagine you're facing a medical emergency and every second counts. In times like these, help needs to come fast, and it needs to know exactly what it's dealing with. This is where AI chatbots, the unsung heroes equipped with artificial intelligence, step in. Picture them as the ever-ready digital responders who jump into action when a health crisis occurs. They're designed to collect critical information, provide immediate guidance, and even soothe frayed nerves while human help is on the way. When someone's heart is pounding with fear and uncertainty, these chatbots offer a calming voice of reason, laying out clear instructions that could be lifesaving.
When Seconds Feel Like Hours
In a heart-clenching moment, punching in a phone number and waiting for a human operator can feel like an eternity. With AI chatbots, the response is virtually instant. They don’t get flustered; they stay cool as a cucumber, asking all the right questions to figure out what's wrong. With every passing second precious, these chatbots can guide a person suffering from symptoms to take potentially life-preserving actions. From administering CPR to identifying the signs of a stroke, they're programmed to help even before medics arrive on the scene, turning bystanders into first responders armed with information and confidence.
Note:  Please don't let using AI or Chatbots stop you from calling 911!
Author Interviews, Technology / 13.12.2023

MedicalResearch.com Interview with: Prof. Enomoto, Masaru Department of Hepatology Graduate School of Medicine Osaka Metropolitan University Osaka, Japan MedicalResearch.com: What is the background for this study? Response: This research was conceived out of the use of generative AI drawing upon past experience in selecting a large amount of literature over an extended amount of time. In recent years, generative AI, such as ChatGPT, has gained attention and is being used in various fields, including information gathering and idea generation. In the medical field in particular, it is challenging to gather pertinent data as the volume of information proliferates on a daily basis, so there is a need to improve the efficiency of information collection.
Author Interviews, Brigham & Women's - Harvard, Gastrointestinal Disease, Obstructive Sleep Apnea, Technology / 18.11.2023

MedicalResearch.com Interview with: [caption id="attachment_61077" align="alignleft" width="150"]Giovanni Traverso MD PhDKarl Van Tassel (1925) Career Development Professor Department of Mechanical Engineering Koch Institute of Integrative Cancer Research Division of Gastroenterology Brigham and Women’s Hospital Harvard Medical School, Boston, MA, USA Dr. Traverso[/caption] Giovanni Traverso MD PhD Karl Van Tassel (1925) Career Development Professor Department of Mechanical Engineering Koch Institute of Integrative Cancer Research Division of Gastroenterology Brigham and Women’s Hospital Harvard Medical School, Boston, MA, USA   MedicalResearch.com: What is the background for this study? Response: I think its always important to acknowledge that this is a big team effort.  We have the teams from MIT, Celero Systems, West Virgnia University (WVU) and Brigham and Women’s Hospital (BWH) all working together on this.   For this study, Celero prototyped the devices that we tested in pre-clinical (Swine) models and in a first-in-human study with the team at WVU. Our lab focuses on the development of ingestible devices for drug delivery and sensing and these have informed the development of these efforts as you can see. MedicalResearch.com: What types of vital signs are measurable in this fashion? Response: Heart rate and respiratory rate.
Breast Cancer, Technology / 22.10.2023

Breast cancer accounts for 12.5% of new annual cases in the world, making it the most common of all cancers. Early detection is vital, since when breast cancer is localized, it boasts a 99% survival rate. Despite this fact, only 64% of breast cancer cases are detected at a localized stage in the US, according to data obtained from the National Breast Cancer Foundation. The good news is that scientists at MIT have developed a new device that can simply be incorporated into a bra. Doing so would allow more frequent monitoring of people with a high risk for breast cancer and it would enable women to detect very early stage tumors.
A Patch In Time
The device is a flexible patch that can be attached to any bra. It has an ultrasound tracker that can analyze breast tissue from various angles—and the images obtained are as high in quality as those obtained from ultrasound probes used in medical imaging clinics The device provides real-time information that is easy to access and interpret. The development of the device resulted from the personal experience of MIT associate professor. Canan Dagdeviren. The latter’s aunt was diagnosed with late-stage breast cancer at the age of 49, passing away six months later. While sitting by her aunt’s bedside, the researchers created a rough schematic of a diagnostic patch that could be incorporated into a brassiere. The aim was to enable women to obtain more frequent information instead of depending on a once-yearly (or less frequent) checkup. Dagdeviren’s device is essentially a miniature 3D-printed ultrasound scanner that has tiny openings. It can be rotated to obtain images from a plethora of angles, and does not require medical expertise to use. The device leverages the very latest technology, including AI algorithms, biomedical systems, and low-power circuits
Author Interviews, Biomarkers, Technology / 06.10.2023

MedicalResearch.com Interview with: [caption id="attachment_60907" align="alignleft" width="125"]HUANYU “LARRY” CHENG Ph.D.Associate Professor and Dorothy Quiggle Career Development Professor in Engineering James L. Henderson, Jr. Memorial Associate Professor of Engineering Science and Mechanics Penn State University Dr. Cheng[/caption] HUANYU “LARRY” CHENG Ph.D. Associate Professor and Dorothy Quiggle Career Development Professor in Engineering James L. Henderson, Jr. Memorial Associate Professor of Engineering Science and Mechanics Penn State University MedicalResearch.com: What is the background for this study? Response: Although increasing efforts have been devoted to the development of non-invasive wearable electrochemical sweat sensors for monitoring physiological and metabolic information, most of them still suffer from poor stability and specificity over time and fluctuating pH and temperatures. laser-induced graphene is the low-cost platform for the early identification and continuous monitoring of different biomarkers for non-invasive disease diagnosis and treatment evaluation However, low sensitivity and limited surface area can limit the detection of ultra-low biomarker concentration in sweat or other fluids. As a result, a wide range of conductive nanomaterials has been incorporated into the porous structure of LIG to increase the available surface area, facilitate electron transfer, and enhance the electrocatalytic activity of the electrode but those nanomaterial modifications are hard to manufacture reproducibly, and they are not long-term stable. Therefore, it is highly desirable to develop a highly sensitive, selective, low-cost, and long-term stable flexible sensing platform for continuous and accurate healthcare monitoring.
Author Interviews, Emergency Care, Technology / 15.09.2023

MedicalResearch.com Interview with: [caption id="attachment_60846" align="alignleft" width="125"]Dr. Hidde ten Berg Department Emergency Medicine Dr. Hidde ten Berg[/caption] Dr. Hidde ten Berg  Department Emergency Medicine and [caption id="attachment_60847" align="alignleft" width="125"]Dr. Steef KurstjensDepartment of Clinical cChemistry and Haematology Dr. Steef Kurstjens[/caption] Dr. Steef Kurstjens Department of Clinical cChemistry and Haematology Jeroen Bosch Hospital, 's-Hertogenbosch, The Netherlands   MedicalResearch.com: What is the background for this study? Response: At this moment we are still in the exploratory phase, and therefore, there is no widespread or routine usage of ChatGPT in Emergency Medicine. That said, there are instances where individual physicians have used ChatGPT for specific purposes. These may include facilitating bureaucratic tasks that can often be time-consuming, aiding in writing e-mails or texts, and serving as a brainstorming tool when dealing with complex medical cases and questions. Though not yet a standardized practice, these isolated examples demonstrate a growing interest for the potential application of this novel technology.
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.