AIMC Topic: Clinical Decision-Making

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Bridging the Gap: Challenges and Strategies for the Implementation of Artificial Intelligence-based Clinical Decision Support Systems in Clinical Practice.

Yearbook of medical informatics
OBJECTIVES: Despite the surge in development of artificial intelligence (AI) algorithms to support clinical decision-making, few of these algorithms are used in practice. We reviewed recent literature on clinical deployment of AI-based clinical decis...

Transforming breast cancer diagnosis and treatment with large language Models: A comprehensive survey.

Methods (San Diego, Calif.)
Breast cancer (BrCa), being one of the most prevalent forms of cancer in women, poses many challenges in the field of treatment and diagnosis due to its complex biological mechanisms. Early and accurate diagnosis plays a fundamental role in improving...

MIO: An ontology for annotating and integrating medical knowledge in myocardial infarction to enhance clinical decision making.

Computers in biology and medicine
As biotechnology and computer science continue to advance, there's a growing amount of biomedical data worldwide. However, standardizing and consolidating these data remains challenging, making analysis and comprehension more difficult. To enhance re...

The AI-enhanced surgeon - integrating black-box artificial intelligence in the operating room.

International journal of surgery (London, England)
New artificial intelligence (AI)/machine learning (ML) technology offers great potential to assist surgeons with real-time intra-operative decision-making. While, AI/ML-driven analysis tools for surgeons currently focus primarily on technical assista...

Evidence-based artificial intelligence: Implementing retrieval-augmented generation models to enhance clinical decision support in plastic surgery.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
The rapid advancement of large language models (LLMs) has generated significant enthusiasm within healthcare, especially in supporting clinical decision-making and patient management. However, inherent limitations including hallucinations, outdated c...

AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study.

Journal of Korean medical science
This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively...

AI-powered model for predicting mortality risk in VA-ECMO patients: a multicenter cohort study.

Scientific reports
Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a critical life support technology for severely ill patients. Despite its benefits, patients face high costs and significant mortality risks. To improve clinical decision-making, this stu...

Large Language Models as Decision-Making Tools in Oncology: Comparing Artificial Intelligence Suggestions and Expert Recommendations.

JCO clinical cancer informatics
PURPOSE: To determine the accuracy of large language models (LLMs) in generating appropriate treatment options for patients with early breast cancer on the basis of their medical records.

Generative artificial intelligence powered chatbots in urology.

Current opinion in urology
PURPOSE OF REVIEW: The integration of artificial intelligence (AI) into healthcare has significantly impacted the way healthcare is delivered, particularly with generative AI-powered chatbots. This review aims to provide an analysis of the applicatio...