AIMC Topic: Decision Support Systems, Clinical

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MultiD4CAD: Multimodal Dataset composed of CT and Clinical Features for Coronary Artery Disease Analysis.

Scientific data
Multimodal datasets offer valuable support for developing Clinical Decision Support Systems (CDSS), which leverage predictive models to enhance clinicians' decision-making. In this observational study, we present a dataset of suspected Coronary Arter...

Artificial intelligence in the prescription of acute medical treatments in primary healthcare - comparison of the performance of family physicians and ChatGPT.

BMC primary care
INTRODUCTION: Artificial intelligence (AI) is increasingly being recognized as a transformative force in healthcare, showing significant promise in supporting healthcare professionals. AI has many applications in healthcare, including providing real-...

Need Analysis of Clinician-Oriented Integrated Precision Oncology Decision Support Tools: Qualitative Descriptive Study.

JMIR human factors
BACKGROUND: The rapid advancement of next-generation sequencing has significantly expanded the landscape of precision medicine. However, health care professionals face increasing challenges in keeping pace with the growing body of oncological knowled...

Visual analysis of research hot topics and trends of clinical decision support system based on CiteSpace.

Langenbeck's archives of surgery
BACKGROUND: Clinical decision support system (CDSS) mainly refers to a computer application system that uses relevant and systematic clinical knowledge and patients' basic information, as well as medical information, to strengthen medical-related dec...

Health-economic evaluation of an AI-powered decision support system for anemia management in in-center hemodialysis patients.

BMC nephrology
BACKGROUND: The Anemia Control Model (ACM) is a decision support system powered by an artificial intelligence core designed to assist nephrologists in managing anemia therapy for in-center hemodialysis (HD) patients. This study aims to evaluate the c...

Artificial Intelligence Applications in Emergency Toxicology: Advancements and Challenges.

Journal of medical Internet research
Emergency toxicology is a complex field requiring rapid and precise decision-making to manage acute poisonings effectively. Toxic exposures are often unpredictable, and the constraints of time and resources often challenge conventional diagnostic and...

Evaluating the Prototype of a Clinical Decision Support System in Primary Care: Qualitative Study.

JMIR formative research
BACKGROUND: General practitioners are confronted with a wide variety of diseases and sometimes diagnostic uncertainty. Clinical decision support systems could be valuable to improve diagnosis, but existing tools are not adapted to the requirements an...

AI-driven multi-modal framework for prognostic modeling in glioblastoma: Enhancing clinical decision support.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
OBJECTIVE: Glioblastoma (GBM) is the most aggressive malignant brain tumor, associated with poor prognosis and limited therapeutic options. Accurate prognostic modeling is essential for guiding personalized treatment strategies. However, existing mod...

Remote clinical decision support tool for Parkinson's disease assessment using a novel approach that combines AI and clinical knowledge.

BMC medical informatics and decision making
BACKGROUND: Early diagnosis of Parkinson's disease (PD) can assist in designing efficient treatments. Reduced facial expressions are considered a hallmark of PD, making advanced artificial intelligence (AI) image processing a potential non-invasive c...