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Decision Support Systems, Clinical

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Clinical and Social Characterization of Patients Hospitalized for COPD Exacerbation Using Machine Learning Tools.

Archivos de bronconeumologia
OBJECTIVE: This study aims to employ machine learning (ML) tools to cluster patients hospitalized for acute exacerbations of chronic obstructive pulmonary disease (COPD) based on their diverse social and clinical characteristics. This clustering is i...

Managing Postembolization Syndrome Through a Machine Learning-Based Clinical Decision Support System: A Randomized Controlled Trial.

Computers, informatics, nursing : CIN
Although transarterial chemoembolization has improved as an interventional method for hepatocellular carcinoma, subsequent postembolization syndrome is a threat to the patients' quality of life. This study aimed to evaluate the effectiveness of a cli...

Towards the Development of the Clinical Decision Support System for the Identification of Respiration Diseases via Lung Sound Classification Using 1D-CNN.

Sensors (Basel, Switzerland)
Respiratory disorders are commonly regarded as complex disorders to diagnose due to their multi-factorial nature, encompassing the interplay between hereditary variables, comorbidities, environmental exposures, and therapies, among other contributing...

Medical diagnosis based on artificial intelligence and decision support system in the management of health development.

Journal of evaluation in clinical practice
BACKGROUND: Medical diagnosis plays a critical role in our daily lives. Every day, over 10 billion cases of both mental and physical health disorders are diagnosed and reported worldwide. To diagnose these disorders, medical practitioners and health ...

[AI-supported decision-making in obstetrics - a feasibility study on the medical accuracy and reliability of ChatGPT].

Zeitschrift fur Geburtshilfe und Neonatologie
The aim of this study is to investigate the feasibility of artificial intelligence in the interpretation and application of medical guidelines to support clinical decision-making in obstetrics. ChatGPT was provided with guidelines on specific obstetr...

Improving Clinical Decision Making With a Two-Stage Recommender System.

IEEE/ACM transactions on computational biology and bioinformatics
Clinical decision-making is complex and time-intensive. To help in this effort, clinical recommender systems (RS) have been designed to facilitate healthcare practitioners with personalized advice. However, designing an effective clinical RS poses ch...

CureMate: A clinical decision support system for breast cancer treatment.

International journal of medical informatics
BACKGROUND: Breast Cancer (BC) poses significant challenges in treatment decision-making. Multiple first treatment lines are currently available, determined by several patient-specific factors that need to be considered in the decision-making process...

Clinical Decision Support and Natural Language Processing in Medicine: Systematic Literature Review.

Journal of medical Internet research
BACKGROUND: Ensuring access to accurate and verified information is essential for effective patient treatment and diagnosis. Although health workers rely on the internet for clinical data, there is a need for a more streamlined approach.

A large language model-based clinical decision support system for syncope recognition in the emergency department: A framework for clinical workflow integration.

European journal of internal medicine
Differentiation of syncope from transient loss of consciousness can be challenging in the emergency department (ED). Natural Language Processing (NLP) enables the analysis of free text in the electronic medical records (EMR). The present paper aimed ...

Integrating Social Determinants of Health in Machine Learning-Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study.

JMIR research protocols
BACKGROUND: The use of both clinical factors and social determinants of health (SDoH) in referral decision-making for case management may improve optimal use of resources and reduce outcome disparities among patients with diabetes.