AIMC Topic: Clinical Decision-Making

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Multiple large language models versus clinical guidelines for postmenopausal osteoporosis: a comparative study of ChatGPT-3.5, ChatGPT-4.0, ChatGPT-4o, Google Gemini, Google Gemini Advanced, and Microsoft Copilot.

Archives of osteoporosis
UNLABELLED: The study assesses the performance of AI models in evaluating postmenopausal osteoporosis. We found that ChatGPT-4o produced the most appropriate responses, highlighting the potential of AI to enhance clinical decision-making and improve ...

Current trends and future prospects of language models and processing systems in spine surgery - a scoping review.

Neurosurgical review
Natural language processing (NLPs) and Large language models (LLM), such as ChatGPT, represent transformative advancements in artificial intelligence (AI). Their implementation into the medical field has a broad potential, and this review discusses t...

Revolutionizing clinical decision making through deep learning and topic modeling for pathway optimization.

Scientific reports
Optimizing clinical pathways is pivotal for enhancing healthcare delivery, yet traditional methods are increasingly insufficient in the face of complex, personalized medical demands. This paper introduces an innovative optimization framework that fus...

Initiation of antifibrotic treatment in fibrosing interstitial lung disease: is the clock ticking till proven progression?

European respiratory review : an official journal of the European Respiratory Society
Several interstitial lung diseases (ILDs) with different aetiologies and pathogenic mechanisms may exhibit a progressive behaviour, similar to idiopathic pulmonary fibrosis, with comparable functional decline and early mortality. Progressive pulmonar...

Evidence Based Gait Analysis Interpretation Tools (EB-GAIT) treatment recommendation and outcome prediction models to support decision-making based on clinical gait analysis data.

PloS one
Clinical gait analysis (CGA) has historically relied on clinician experience and judgment, leading to modest, stagnant, and unpredictable outcomes. This paper introduces Evidence-Based Gait Analysis Interpretation Tools (EB-GAIT), a novel framework l...

Evaluating Large Language Models for imaging modality selection: Potential to reduce unnecessary contrast agent use and radiation exposure.

Clinical imaging
INTRODUCTION: Large Language Models (LLMs) represent a transformative leap in artificial intelligence with the potential to revolutionize radiologic decision-making. This study uniquely evaluates the performance of various LLMs from different vendors...

A practical approach to predicting long-term outcomes in traumatic brain injury: Enhancing clinical decision-making with machine learning.

Computers in biology and medicine
BACKGROUND: Traumatic brain injury (TBI) is among the most prevalent causes of emergency department visits globally. TBI leads to high morbidity and mortality rates, which poses a noteworthy burden on the medical system regarding both patients and ec...

When time is of the essence: ethical reconsideration of XAI in time-sensitive environments.

Journal of medical ethics
The objective of explainable artificial intelligence systems designed for clinical decision support (XAI-CDSS) is to enhance physicians' diagnostic performance, confidence and trust through the implementation of interpretable methods, thus providing ...

Explainable artificial intelligence: enhancing decision-making in plastic surgery.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Artificial intelligence (AI) models increasingly influence plastic surgery practice through risk prediction, outcome forecasting, and treatment planning. However, their "black box" nature often prevents surgeons from understanding the reasoning behin...