AIMC Topic: Clinical Decision-Making

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An FDG-PET-Based Machine Learning Framework to Support Neurologic Decision-Making in Alzheimer Disease and Related Disorders.

Neurology
BACKGROUND AND OBJECTIVES: Distinguishing neurodegenerative diseases is a challenging task requiring neurologic expertise. Clinical decision support systems (CDSSs) powered by machine learning (ML) and artificial intelligence can assist with complex ...

Exploring the medical ethical limitations of GPT-4 in clinical decision-making scenarios: a pilot survey.

Frontiers in public health
BACKGROUND: This study aims to conduct an examination of GPT-4's tendencies when confronted with ethical dilemmas, as well as to ascertain their ethical limitations within clinical decision-makings.

Predicting Immunotherapy Response in Unresectable Hepatocellular Carcinoma: A Comparative Study of Large Language Models and Human Experts.

Journal of medical systems
Hepatocellular carcinoma (HCC) is an aggressive cancer with limited biomarkers for predicting immunotherapy response. Recent advancements in large language models (LLMs) like GPT-4, GPT-4o, and Gemini offer the potential for enhancing clinical decisi...

Enhancing clinical decision-making in closed pelvic fractures with machine learning models.

Biomolecules & biomedicine
Closed pelvic fractures can lead to severe complications, including hemodynamic instability (HI) and mortality. Accurate prediction of these risks is crucial for effective clinical management. This study aimed to utilize various machine learning (ML)...

Evaluation of the performance of large language models in clinical decision-making in endodontics.

BMC oral health
BACKGROUND: Artificial intelligence (AI) chatbots are excellent at generating language. The growing use of generative AI large language models (LLMs) in healthcare and dentistry, including endodontics, raises questions about their accuracy. The poten...

Advancing lung transplantation through machine learning and artificial intelligence.

Current opinion in pulmonary medicine
PURPOSE OF REVIEW: To explore the current applications of artificial intelligence and machine learning in lung transplantation, including outcome prediction, drug dosing, and the potential future uses and risks as the technology continues to evolve.

Protocol of the pilot study to test and evaluate the iCARE tool: a machine learning-based e-platform tool to make health prognoses and support decision-making for the care of older persons with complex chronic conditions.

BMJ open
INTRODUCTION: The provision of optimal care for older adults with complex chronic conditions (CCCs) poses significant challenges due to the interplay of multiple medical, pharmacological, functional and psychosocial factors. To address these challeng...

The Use of an Artificial Intelligence Platform OpenEvidence to Augment Clinical Decision-Making for Primary Care Physicians.

Journal of primary care & community health
BACKGROUND: Artificial intelligence (AI) platforms can potentially enhance clinical decision-making (CDM) in primary care settings. OpenEvidence (OE), an AI tool, draws from trusted sources to generate evidence-based medicine (EBM) recommendations to...

Comparative evaluation of artificial intelligence models GPT-4 and GPT-3.5 in clinical decision-making in sports surgery and physiotherapy: a cross-sectional study.

BMC medical informatics and decision making
BACKGROUND: The integration of artificial intelligence (AI) in healthcare has rapidly expanded, particularly in clinical decision-making. Large language models (LLMs) such as GPT-4 and GPT-3.5 have shown potential in various medical applications, inc...

The Role of ChatGPT in osteoporosis management: a comparative analysis with clinical expertise.

Archives of osteoporosis
UNLABELLED: This study evaluates the role of ChatGPT in osteoporosis management, demonstrating 91% diagnostic accuracy and significantly faster response times compared to clinicians. The findings highlight the potential for artificial intelligence (A...