Evidence regarding the association between physical activity and Parkinson’s disease (PD) risk is generally limited due to the use of self-report questionnaires. We aimed to quantify the separate and combined effects of accelerometer-measured light…
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It is uncommon for risk groups defined by statistical or artificial intelligence (AI) models to be chosen by jointly considering model performance and potential interventions available. We develop a framework to rapidly guide choice…
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At the Radiological Society of North America conference this week in Chicago, Konica Minolta Healthcare Americas is among many companies showcasing new artificial intelligence tools for imaging and clinical decision support.WHY IT MATTERS
Konica Minolta announced…
Chronic obstructive pulmonary disease (COPD) is the third leading cause of death and is associated with multiple medical and psychological comorbidities. Therefore, future strategies to improve COPD management and outcomes are needed for the…
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OpenAI’s GPT-4 correctly diagnosed 52.7% of complex challenge cases, compared to 36% of medical journal readers, and outperformed 99.98% of simulated human readers, according to a study published by the New England Journal of Medicine.The…
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This scoping review focuses on the essential role of models for causal inference in shaping actionable artificial intelligence (AI) designed to aid clinicians in decision-making. The objective was to identify and evaluate the reporting…
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Machine learning and deep learning are two subsets of artificial intelligence that involve teaching computers to learn and make decisions from any sort of data. Most recent developments in artificial intelligence are coming from…
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The integration of Quality Management System (QMS) principles into the life cycle of development, deployment, and utilization of machine learning (ML) and artificial intelligence (AI) technologies within healthcare settings holds the potential to close…
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The effectiveness of lifestyle interventions in reducing caloric intake and increasing physical activity for preventing Type 2 Diabetes (T2D) has been previously demonstrated. The use of modern technologies can potentially further improve the success…
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Randomized clinical trials (RCT) represent the cornerstone of evidence-based medicine but are resource-intensive. We propose and evaluate a machine learning (ML) strategy of adaptive predictive enrichment through computational trial phenomaps to optimize RCT enrollment….
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