There are over 7000 rare diseases, some affecting 3500 or fewer patients in the United States. Due to clinicians’ limited experience with such diseases and the heterogeneity of clinical presentations, ~70% of individuals seeking…
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Understanding surgical data in real-time will lead to improved feedback, learning, and performance for surgeons. This is important as data-driven systems offer safer, more standardized surgery, and faster training times. Artificial intelligence shows great…
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AI is popping up everywhere in healthcare. The problem is that there is a lot of vaporware out there which talks of leveraging AI, but hasn’t actually implemented it yet. That’s why it was…
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Stroke remains a leading global cause of mortality, with ischemic stroke as the most common subtype. Atrial fibrillation (AF) increases ischemic stroke risk due to thrombus formation in the left atrium (LA), particularly in…
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Reproductive aging impacts women’s health through fertility decline, disease susceptibility, and systemic aging. This study explores the retinal age gap—the difference between predicted retinal age and chronological age—as a novel biomarker for reproductive aging….
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As digital biomarkers gain traction in Alzheimer’s disease (AD) diagnosis, understanding recent advancements is crucial. This review conducts a bibliometric analysis of 431 studies from five online databases: Web of Science, PubMed, Embase, IEEE…
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The widespread adoption of Electronic Health Records (EHRs) and deep learning, particularly through Self-Supervised Representation Learning (SSRL) for categorical data, has transformed clinical decision-making. This scoping review, following PRISMA-ScR guidelines, examines 46 studies published…
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Accurate detection of Parkinson’s disease (PD) through speech analysis holds great promise for early diagnosis and improved patient management. However, developing robust machine learning models is challenging due to the decentralized nature of medical…
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We explore biases present in publicly available fetal ultrasound (US) imaging datasets, currently at the disposal of researchers to train deep learning (DL) algorithms for prenatal diagnostics. As DL increasingly permeates the field of…
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A new AI model that is capable of simultaneous analysis of different skin images can potentially improve the diagnostic accuracy of both dermatology and non-dermatology professionals. An international research team led by AI and machine…
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