#AIhealthcare Tag

14 Jul

Posted at 11:57h in AI and HealthCare

Medical devices are revolutionizing modern healthcare. It's not surprising to see the growth this particular market is witnessing in recent times. Fortune Business Insights reports that the global medical devices market was valued at $572.31 billion in 2025. It is projected to expand further to $604.99 billion in 2026. Rising inpatient admissions and increasing surgical procedures fuel this market growth.

On the other hand, artificial intelligence is also transforming healthcare faster than many people expected. However, bringing AI into medical devices involves much more than writing advanced software. Every system must perform reliably because people's health depends on accurate results. For a broader view of how AI is reshaping clinical data and decision-making, see this overview of AI and healthcare data: turning numbers into action.

[caption id="attachment_74975" align="aligncenter" width="500"]challenges_of_integrating_ai_into_medical_devices Pexels image[/caption]

24 Jun

Posted at 14:23h in Medical Records, Technology
The phrase "custom AI solutions for healthcare" has been stretched to cover everything from a chatbot that answers FAQ questions to a clinician-reviewed diagnostic model trained on 10 million labeled images. That spectrum matters for vendor selection, because the right company for a conversational patient engagement tool is categorically different from the right company for a radiology AI system. This guide focuses on companies building meaningful custom AI — systems that process clinical data, generate outputs that influence care or operations, and operate under regulatory frameworks that hold their developers accountable for what those outputs say. Seven companies are profiled, each evaluated with a Strengths / Limitations / Verdict framework that gives you a direct, unhedged read on what each company does well and where it falls short.

23 May

Posted at 19:37h in AI and HealthCare, Mental Health Research
[caption id="attachment_73932" align="aligncenter" width="500"]AI in Mental Health pexels Photo by cottonbro studio[/caption] Editor's note: This piece discusses mental health issues. If you have experienced suicidal thoughts or have lost someone to suicide and want to seek help, you can contact the Crisis Text Line by texting "START" to 741-741 or call the Suicide Prevention Lifeline at 800-273-8255. The application of artificial intelligence (AI) in mental health care is growing, providing novel solutions to the diagnosis, tracking, and management of mental health conditions. AI has great potential to increase the efficiency and accessibility of mental health care, from chatbots that offer emotional support to tools that identify early indicators of depression and anxiety. But these advantages also come with significant risks and ethical issues such as emotional safety, accuracy, and privacy. The possibilities and difficulties of AI in mental health are examined in this article, emphasising the necessity of its ethical and responsible application.

22 May

Posted at 10:31h in Electronic Records
A recent clinic audit showed primary care physicians spending 145.9 minutes a day in the electronic health record, or EHR. That total included 60.7 minutes of after-hours work and 42.9 minutes on notes alone. That is nearly two and a half hours each day spent documenting instead of treating patients. A large share of that time is recoverable. Voice-based documentation, now improved by ambient and generative AI, can cut documentation time, improve note completeness, and reduce after-hours work. That matters whether your team already uses speech recognition or still types every note. The gap between efficient and inefficient documentation workflows is now wide enough to affect access, revenue, and burnout. This workflow now includes real-time speech recognition, back-end transcription, human scribes, and ambient AI that drafts notes from the room conversation. The practical challenge is choosing the right method, then building enough review and compliance control to use it safely. Clinics that set baselines, train staff, and track edits tend to see the fastest gains. Clinics that skip those steps usually trade typing time for editing time.

01 May

Posted at 15:17h in AI and HealthCare, Electronic Records
[caption id="attachment_73576" align="aligncenter" width="500"]AI is Improving Physician Productivity Pexels[/caption] Doctors work long hours, but surprisingly, much of that time is not dedicated to patient care — it goes to administrative work. According to American Medical Association data from 2024, physicians work 57.8 hours per week. Of those, 27 hours go to patient care and 13 hours to indirect care. The rest is spent on admin-related tasks. In simple words, physicians are spending almosst more time on computers than on patient care. This is the core problem every medical practice is facing today, and AI-powered tools claim to fix it.