Despite significant advances, the prevention and management of cardiovascular disease remain challenging, especially for ischemic heart disease (IHD). Current clinical decision-making relies heavily on physician expertise, guideline-directed therapies, and static risk scores, which often…
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What You Should Know:
– ConcertAI announced a multi-year agreement with Bayer to leverage ConcertAI’s Translational360™ and AI SaaS solutions, which use artificial intelligence and machine learning (AI/ML)-derived insights to accelerate clinical development in precision…
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What You Should Know:
– A new report from KLAS Research examines the use of artificial intelligence (AI) and machine learning (ML) within healthcare data science solutions.
– The KLAS report, which builds upon a previous…
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Alarming Gaps in Healthcare AI Detection
New research published in Nature Communications Medicine has exposed critical flaws in machine learning mortality prediction models currently used in healthcare settings. These AI systems failed to recognize approximately…
Attention-deficit/hyperactivity disorder (ADHD), characterized by diagnostic complexity and symptom heterogeneity, is a prevalent neurodevelopmental disorder. Here, we explored the machine learning (ML) analysis of retinal fundus photographs as a noninvasive biomarker for ADHD screening…
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Musculoskeletal complaints account for 30% of GP consultations, with many referred to rheumatology clinics via letters. This study developed a Machine Learning (ML) pipeline to prioritize referrals by identifying rheumatoid arthritis (RA), osteoarthritis, fibromyalgia,…
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The confluence of new technologies with artificial intelligence (AI) and machine learning (ML) analytical techniques is rapidly advancing the field of precision oncology, promising to improve diagnostic approaches and therapeutic strategies for patients with…
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Noninvasive methods for intracranial pressure (ICP) monitoring have emerged, but none has successfully replaced invasive techniques. This observational study developed and tested a machine learning (ML) model to estimate ICP using waveforms from a…
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While machine learning (ML)-based solutions—often referred to as artificial intelligence (AI) solutions—have demonstrated comparable or superior performance to human experts across various healthcare applications, their vulnerability to perturbations and stability to variations due to…
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Machine learning has increasingly been applied to predict opioid-related harms due to its ability to handle complex interactions and generating actionable predictions. This review evaluated the types and quality of ML methods in opioid…
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