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Clinical Decision-Making

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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.

Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Decisions on the best available treatment in clinical oncology are based on expert opinions in multidisciplinary cancer conferences (MCC). Artificial intelligence (AI) could increase evidence-based treatment by generating additional treat...

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...

Artificial intelligence in gastroenterology: Ethical and diagnostic challenges in clinical practice.

World journal of gastroenterology
This article discusses the manuscript recently published in the , which explores the application of deep learning models in decision-making processes via wireless capsule endoscopy. Integrating artificial intelligence (AI) into gastrointestinal disea...

Do Treatment Choices by Artificial Intelligence Correspond to Reality? Retrospective Comparative Research with Necrotizing Enterocolitis as a Use Case.

Medical decision making : an international journal of the Society for Medical Decision Making
BackgroundIn cases of surgical necrotizing enterocolitis (NEC), the choice between laparotomy (LAP) or comfort care (CC) presents a complex, ethical dilemma. A behavioral artificial intelligence technology (BAIT) decision aid was trained on expert kn...

An intelligent multi-attribute decision-making system for clinical assessment of spinal cord disorder using fuzzy hypersoft rough approximations.

BMC medical informatics and decision making
The data for diagnosing spinal cord disorder (SCD) are complex and often confusing, making it difficult for established diagnostic techniques to yield reliable results. This issue frequently necessitates expensive testing to get an accurate diagnosis...

AI-Driven decision-making for personalized elderly care: a fuzzy MCDM-based framework for enhancing treatment recommendations.

BMC medical informatics and decision making
BACKGROUND: Global healthcare systems face enormous challenges due to the ageing population, demanding novel measures to assure long-term efficacy and viability. The expanding senior population, which requires specialised and efficient healthcare sol...

NLP modeling recommendations for restricted data availability in clinical settings.

BMC medical informatics and decision making
BACKGROUND: Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. Natural Language Processing (NLP) has emerged as a promising solution, but its application in cl...