AIMC Topic: Decision Support Systems, Clinical
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Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence.
Nature cancer
Jan 30, 2025
Despite advances in precision oncology, clinical decision-making still relies on limited variables and expert knowledge. To address this limitation, we combined multimodal real-world data and explainable artificial intelligence (xAI) to introduce AI-...
User-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Protocol for a Multimethod Research Project.
JMIR research protocols
Jan 30, 2025
BACKGROUND: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, t...
Intricacies of human-AI interaction in dynamic decision-making for precision oncology.
Nature communications
Jan 29, 2025
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics...
Non-experimental rapid identification of lower respiratory tract infections in patients with chronic obstructive pulmonary disease using multi-label learning.
Computer methods and programs in biomedicine
Jan 27, 2025
BACKGROUND AND OBJECTIVE: Microbiological culture is a standard diagnostic test that takes a long time to identify lower respiratory tract infections (LRTI) in patients with chronic obstructive pulmonary disease (COPD). This study entailed the develo...
The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.
Journal of medical Internet research
Jan 24, 2025
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
Jan 24, 2025
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
Jan 21, 2025
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
Jan 20, 2025
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
Jan 18, 2025
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
Jan 7, 2025
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...
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