AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Artificial intelligence in rheumatology: perspectives and insights from a nationwide survey of U.S. rheumatology fellows.

Rheumatology international
Artificial Intelligence (AI) is poised to revolutionize healthcare by enhancing clinical practice, diagnostics, and patient care. Although AI offers potential benefits through data-driven insights and personalized treatments, challenges related to im...

Identifying cardiovascular disease risk in the U.S. population using environmental volatile organic compounds exposure: A machine learning predictive model based on the SHAP methodology.

Ecotoxicology and environmental safety
BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of mortality globally. Environmental pollutants, specifically volatile organic compounds (VOCs), have been identified as significant risk factors. This study aims to develop a machine l...

ChatGPT-4 extraction of heart failure symptoms and signs from electronic health records.

Progress in cardiovascular diseases
BACKGROUND: Natural language processing (NLP) can facilitate research utilizing data from electronic health records (EHRs). Large language models can potentially improve NLP applications leveraging EHR notes. The objective of this study was to assess...

Impact of a clinical pharmacist-led, artificial intelligence-supported medication adherence program on medication adherence performance, chronic disease control measures, and cost savings.

Journal of the American Pharmacists Association : JAPhA
BACKGROUND: Chronic diseases are the leading cause of disability and death in the United States. Clinical pharmacists have been shown to optimize health outcomes and reduce health care expenditures in patients with chronic diseases through improving ...

Clinically Guided Adaptive Machine Learning Update Strategies for Predicting Severe COVID-19 Outcomes.

The American journal of medicine
BACKGROUND: Machine learning algorithms are essential for predicting severe outcomes during public health crises like COVID-19. However, the dynamic nature of diseases requires continual evaluation and updating of these algorithms. This study aims to...

Unveiling livestock trade trends: A beginner's guide to generative AI-powered visualization.

Research in veterinary science
This tutorial, rooted in the context of livestock research, is designed to assist novice or non-programmers in visualizing trends in livestock exports between the US and Japan using Python and generative AI systems such as Microsoft's Copilot and Goo...

De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.

Clinical orthopaedics and related research
BACKGROUND: Available codes in the ICD-10 do not accurately reflect soft tissue sarcoma diagnoses, and this can result in an underrepresentation of soft tissue sarcoma in databases. The National VA Database provides a unique opportunity for soft tiss...

Development of a Predictive Hospitalization Model for Skilled Nursing Facility Patients.

Journal of the American Medical Directors Association
OBJECTIVES: Identifying skilled nursing facility (SNF) patients at risk for hospitalization or death is of interest to SNFs, patients, and patients' families because of quality measures, financial penalties, and limited clinical staffing. We aimed to...

Identifying predictors of multi-year cannabis vaping in U.S. Young adults using machine learning.

Addictive behaviors
INTRODUCTION: Increasing number of current cannabis users report using a vaporized form of cannabis and young adults are most likely to vape cannabis. However, the number of studies on cannabis vaping is limited, and predictors of cannabis vaping amo...