Medication-related harm has a significant impact on global healthcare costs and patient outcomes. Generative artificial intelligence (GenAI) and large language models (LLM) have emerged as a promising tool in mitigating risks of medication-related harm….
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Building accurate prediction models and identifying predictive biomarkers for treatment response in Muscle-Invasive Bladder Cancer (MIBC) are essential for improving patient survival but remain challenging due to tumor heterogeneity, despite numerous related studies. To…
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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…
Pediatric health system Connecticut Children’s is expanding its partnership with Xerox by introducing an AI-powered offering aimed at streamlining care delivery while improving patient outcomes.Hartford-based Connecticut Children’s is utilizing AI to allow emergency department…
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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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Current clinician-based and automated risk assessment methods treat the risk of suicide-related behaviors (SRBs) as static, while in actual clinical practice, SRB risk fluctuates over time. Here, we develop two closely related model classes,…
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Low-dose computed tomography attenuation correction (CTAC) scans are used in hybrid myocardial perfusion imaging (MPI) for attenuation correction and coronary calcium scoring, and contain additional anatomic and pathologic information not utilized in clinical assessment….
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Researchers from one of South Korea’s largest hospitals claim to have developed an objective measure of pain during and after surgery using AI. FINDINGS
The research team at Asan Medical Center devised a pain assessment model…
Molecular subtyping and grading of adult-type diffuse gliomas are essential for treatment decisions and patient prognosis. We introduce GlioMT, an interpretable multimodal transformer that integrates imaging and clinical data to predict the molecular subtype…
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Electroconvulsive therapy (ECT) and ketamine are effective treatments for depression; however, evidence-based guidelines are needed to inform individual treatment selection. We adapted the Personalized Advantage Index (PAI) using machine learning to predict optimal treatment…
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