AIMC Topic: Decision Support Systems, Clinical

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Artificial intelligence-based clinical decision support in pediatrics.

Pediatric research
Machine learning models may be integrated into clinical decision support (CDS) systems to identify children at risk of specific diagnoses or clinical deterioration to provide evidence-based recommendations. This use of artificial intelligence models ...

Identification of Preanesthetic History Elements by a Natural Language Processing Engine.

Anesthesia and analgesia
BACKGROUND: Methods that can automate, support, and streamline the preanesthesia evaluation process may improve resource utilization and efficiency. Natural language processing (NLP) involves the extraction of relevant information from unstructured t...

Prediction of postoperative cardiac events in multiple surgical cohorts using a multimodal and integrative decision support system.

Scientific reports
Postoperative patients are at risk of life-threatening complications such as hemodynamic decompensation or arrhythmia. Automated detection of patients with such risks via a real-time clinical decision support system may provide opportunities for earl...

Sample Size Calculation for Clinical Trials of Medical Decision Support Systems with Binary Outcome.

Sovremennye tekhnologii v meditsine
Currently, software products for use in medicine are actively developed. Among them, the dominant share belongs to clinical decision support systems (CDSS), which can be intelligent (based on mathematical models obtained by machine learning methods o...

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.

BMJ (Clinical research ed.)
A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluat...

Predictive models for clinical decision making: Deep dives in practical machine learning.

Journal of internal medicine
The deployment of machine learning for tasks relevant to complementing standard of care and advancing tools for precision health has gained much attention in the clinical community, thus meriting further investigations into its broader use. In an int...

Charting the potential of brain computed tomography deep learning systems.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Brain computed tomography (CTB) scans are widely used to evaluate intracranial pathology. The implementation and adoption of CTB has led to clinical improvements. However, interpretation errors occur and may have substantial morbidity and mortality i...

Digital Health Policy and Programs for Hospital Care in Vietnam: Scoping Review.

Journal of medical Internet research
BACKGROUND: There are a host of emergent technologies with the potential to improve hospital care in low- and middle-income countries such as Vietnam. Wearable monitors and artificial intelligence-based decision support systems could be integrated wi...

An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus.

Scientific reports
Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal and neonatal consequences, is increased in mothers with overweight and obesity. Interventions initiated early in pregnancy can reduce the rate of GDM i...

A Clinical Decision Support System for Sleep Staging Tasks With Explanations From Artificial Intelligence: User-Centered Design and Evaluation Study.

Journal of medical Internet research
BACKGROUND: Despite the unprecedented performance of deep learning algorithms in clinical domains, full reviews of algorithmic predictions by human experts remain mandatory. Under these circumstances, artificial intelligence (AI) models are primarily...