AIMC Topic: Decision Support Systems, Clinical

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How to Evaluate the Accuracy of Symptom Checkers and Diagnostic Decision Support Systems: Symptom Checker Accuracy Reporting Framework (SCARF).

JMIR human factors
Symptom checkers are apps and websites that assist medical laypeople in diagnosing their symptoms and determining which course of action to take. When evaluating these tools, previous studies primarily used an approach introduced a decade ago that la...

A Review of Recent Developments in Artificial Intelligence and Big Data Technologies for Ophthalmology Referrals and Clinical Practice.

Medical science monitor : international medical journal of experimental and clinical research
Ophthalmology is undergoing rapid transformation through the integration of smart technologies such as artificial intelligence (AI), big data analytics, and clinical decision support systems (CDSS). With increasing pressure to improve clinical effici...

Systematic evaluation of deepseek in urolithiasis: from medical knowledge to clinical decision support.

World journal of urology
BACKGROUND: Large language models (LLMs), such as ChatGPT, have demonstrated promising potential in medical knowledge retrieval and clinical decision support. DeepSeek, a China-developed model released in 2025, has been proposed as a medical AI tool,...

An approach to make general practitioner referrals suitable for artificial intelligence deployment.

The New Zealand medical journal
Outpatient referrals for hospital specialist assessment are an increasing workload that carry significant risk if not attended to in a timely manner. This viewpoint discusses how decision support (including artificial intelligence and machine learnin...

Study protocol for optimising antipsychotic prescribing among hospitalised patients in the acute care setting in Scotland: a national retrospective cohort study.

BMJ open
INTRODUCTION: Prescribing high-dose antipsychotics is typically reserved for individuals with treatment-resistant severe mental illnesses, such as schizophrenia, bipolar disorder and psychotic depression. It carries an increased risk of adverse drug ...

COVID-19 severity analysis for clinical decision support based on machine learning approach.

Scientific reports
The COVID-19 pandemic has placed immense pressure on global healthcare systems, underscoring the urgent need for early and accurate prediction of disease severity to improve patient care and optimize resource allocation. Failure in ward allocation ca...

High Concordance Between GPT-4o and Multidisciplinary Tumor Board Decisions in Breast Cancer: A Retrospective Decision Support Analysis.

Journal of medical systems
Large language models (LLMs) such as ChatGPT have gained attention for their potential to assist clinical decision-making in oncology. However, real-world validation of these models against multidisciplinary tumor board (MTB) recommendations-particul...

AI-Assisted Cardiovascular Risk Assessment by General Practitioners in Resource-Constrained Indonesian Settings Using a Conceptual Prototype: Randomized Controlled Study.

Journal of medical Internet research
BACKGROUND: Preventive strategies integrated with digital health and artificial intelligence (AI) have significant potential to mitigate the global burden of atherosclerotic cardiovascular disease (ASCVD). AI-enabled clinical decision support (CDS) s...

AI-driven clinical decision support for early diagnosis and treatment planning in patients with suspected sleep apnea using clinical and demographic data before sleep studies.

NPJ primary care respiratory medicine
OBJECTIVE: This study explored the application of Machine Learning (ML) techniques to cluster patients with suspected sleep apnea (SA), based on clinical-demographic data, with the aim of optimizing diagnostic pathways and enabling more personalized ...

Large language model as a clinical decision support tool in the initial management of critically ill children: a pilot evaluation.

European journal of pediatrics
UNLABELLED: Large language models (LLMs) like ChatGPT are being explored as clinical decision support tools, but their reliability in pediatric acute care remains uncertain. This pilot study assessed ChatGPT-4.0's performance in the early management ...