AIMC Topic: Decision Support Techniques

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Prehospital triage of trauma patients: predicting major surgery using artificial intelligence as decision support.

The British journal of surgery
BACKGROUND: Matching the necessary resources and facilities to attend to the needs of trauma patients is traditionally performed by clinicians using criteria-directed triage protocols. In the present study, it was hypothesized that an artificial inte...

The role of product art design based on a fuzzy decision support system in improving user interaction experience.

PloS one
User interaction for product selection relies on its design and technical support to improve the quality of the experience. Decision support systems are incorporated to leverage user experience through product interactions. This article introduces an...

Translating promise into practice: a review of machine learning in suicide research and prevention.

The lancet. Psychiatry
In ever more pressured health-care systems, technological solutions offering scalability of care and better resource targeting are appealing. Research on machine learning as a technique for identifying individuals at risk of suicidal ideation, suicid...

Decision support model for the patient admission scheduling problem based on picture fuzzy aggregation information and TOPSIS methodology.

Mathematical biosciences and engineering : MBE
Health care systems around the world do not have sufficient medical services to immediately offer elective (e.g., scheduled or non-emergency) services to all patients. The goal of patient admission scheduling (PAS) as a complicated decision making is...

A Novel Predictive Model for Anastomotic Leakage in Colorectal Cancer Using Auto-artificial Intelligence.

Anticancer research
AIM: Anastomotic leakage (AL) in left-sided colorectal cancer is a serious complication, with an incidence rate of 6-18%. We developed a novel predictive model for AL in colorectal surgery with double-stapling technique (DST) anastomosis using auto-a...

Development and Validation of a Machine Learning-Based Decision Support Tool for Residency Applicant Screening and Review.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: Residency programs face overwhelming numbers of residency applications, limiting holistic review. Artificial intelligence techniques have been proposed to address this challenge but have not been created. Here, a multidisciplinary team sough...