AIMC Topic: Decision Support Systems, Clinical

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The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.

Journal of medical Internet research
BACKGROUND: Recent advancements in artificial intelligence (AI) have changed the care processes in mental health, particularly in decision-making support for health care professionals and individuals with mental health problems. AI systems provide su...

AI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study.

Journal of medical Internet research
BACKGROUND: Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide deaths in 2017. Although the Sequential Organ Failure Assessment (SOFA) score standardizes the diagnosis of organ dysfunction, early sepsis detection...

A Novel Deep Ensemble Method for Selective Classification of Electrocardiograms.

IEEE transactions on bio-medical engineering
OBJECTIVE: Telehealth paradigms are essential for remotely managing patients with chronic conditions. To assist clinicians in handling the large volumes of data collected through these systems, clinical decision support systems (CDSSs) have been deve...

Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions.

BMC medical informatics and decision making
BACKGROUND: Post bariatric hypoglycaemic (PBH) is a late complication of weight loss surgery, characterised by critically low blood glucose levels following meal-induced glycaemic excursions. The disabling consequences of PBH underline the need for t...

The efficiency of artificial intelligence for management and clinical decision-making in the identification of patients with hidden HCV infection (Intelligen-C strategy).

Gastroenterologia y hepatologia
INTRODUCTION: Artificial intelligence (AI) allows the optimization of diagnostic processes for hepatitis C virus (HCV) patients. Our objective was to evaluate the clinical, economic, and management benefits of an AI-based clinical decision support sy...

Rad4XCNN: A new agnostic method for post-hoc global explanation of CNN-derived features by means of Radiomics.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In recent years, machine learning-based clinical decision support systems (CDSS) have played a key role in the analysis of several medical conditions. Despite their promising capabilities, the lack of transparency in AI mode...

The Willingness of Doctors to Adopt Artificial Intelligence-Driven Clinical Decision Support Systems at Different Hospitals in China: Fuzzy Set Qualitative Comparative Analysis of Survey Data.

Journal of medical Internet research
BACKGROUND: Artificial intelligence-driven clinical decision support systems (AI-CDSSs) are pivotal tools for doctors to improve diagnostic and treatment processes, as well as improve the efficiency and quality of health care services. However, not a...

Artificial Intelligence in Physical Therapy: Evaluating ChatGPT's Role in Clinical Decision Support for Musculoskeletal Care.

Annals of biomedical engineering
BACKGROUND: The integration of artificial intelligence into medicine has attracted increasing attention in recent years. ChatGPT has emerged as a promising tool for delivering evidence-based recommendations in various clinical domains. However, the a...

Issues and Limitations on the Road to Fair and Inclusive AI Solutions for Biomedical Challenges.

Sensors (Basel, Switzerland)
OBJECTIVE: In this paper, we explore the correlation between performance reporting and the development of inclusive AI solutions for biomedical problems. Our study examines the critical aspects of bias and noise in the context of medical decision sup...