AI Medical Compendium Topic

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Clinical Decision-Making

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Development and Validation of an Interpretable Conformal Predictor to Predict Sepsis Mortality Risk: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Early and reliable identification of patients with sepsis who are at high risk of mortality is important to improve clinical outcomes. However, 3 major barriers to artificial intelligence (AI) models, including the lack of interpretabilit...

Generative AI in healthcare: an implementation science informed translational path on application, integration and governance.

Implementation science : IS
BACKGROUND: Artificial intelligence (AI), particularly generative AI, has emerged as a transformative tool in healthcare, with the potential to revolutionize clinical decision-making and improve health outcomes. Generative AI, capable of generating n...

Evaluation of AI-generated responses by different artificial intelligence chatbots to the clinical decision-making case-based questions in oral and maxillofacial surgery.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: This study aims to evaluate the correctness of the generated answers by Google Bard, GPT-3.5, GPT-4, Claude-Instant, and Bing chatbots to decision-making clinical questions in the oral and maxillofacial surgery (OMFS) area.

Using natural language processing to analyze unstructured patient-reported outcomes data derived from electronic health records for cancer populations: a systematic review.

Expert review of pharmacoeconomics & outcomes research
INTRODUCTION: Patient-reported outcomes (PROs; symptoms, functional status, quality-of-life) expressed in the 'free-text' or 'unstructured' format within clinical notes from electronic health records (EHRs) offer valuable insights beyond biological a...

Development of a machine learning-based model for predicting individual responses to antihypertensive treatments.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: Personalized antihypertensive drug selection is essential for optimizing hypertension management. The study aimed to develop a machine learning (ML) model to predict individual blood pressure (BP) responses to different antihyper...

Utility of artificial intelligence-based large language models in ophthalmic care.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
PURPOSE: With the introduction of ChatGPT, artificial intelligence (AI)-based large language models (LLMs) are rapidly becoming popular within the scientific community. They use natural language processing to generate human-like responses to queries....

Potential applications and implications of large language models in primary care.

Family medicine and community health
The recent release of highly advanced generative artificial intelligence (AI) chatbots, including ChatGPT and Bard, which are powered by large language models (LLMs), has attracted growing mainstream interest over its diverse applications in clinical...

A systematic review of the application of deep learning techniques in the physiotherapeutic therapy of musculoskeletal pathologies.

Computers in biology and medicine
Physiotherapy is a critical area of healthcare that involves the assessment and treatment of physical disabilities and injuries. The use of Artificial Intelligence (AI) in physiotherapy has gained significant attention due to its potential to enhance...