AIMC Topic: Decision Support Systems, Clinical

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Clinician involvement in research on machine learning-based predictive clinical decision support for the hospital setting: A scoping review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to describe the prevalence and nature of clinical expert involvement in the development, evaluation, and implementation of clinical decision support systems (CDSSs) that utilize machine learning to analyze electronic healt...

Development of a "meta-model" to address missing data, predict patient-specific cancer survival and provide a foundation for clinical decision support.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Like most real-world data, electronic health record (EHR)-derived data from oncology patients typically exhibits wide interpatient variability in terms of available data elements. This interpatient variability leads to missing data and can...

Clinical decision support system, using expert consensus-derived logic and natural language processing, decreased sedation-type order errors for patients undergoing endoscopy.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Determination of appropriate endoscopy sedation strategy is an important preprocedural consideration. To address manual workflow gaps that lead to sedation-type order errors at our institution, we designed and implemented a clinical decisi...

The Effectiveness of a Deep Learning Model to Detect Left Ventricular Systolic Dysfunction from Electrocardiograms.

International heart journal
Deep learning models can be applied to electrocardiograms (ECGs) to detect left ventricular (LV) dysfunction. We hypothesized that applying a deep learning model may improve the diagnostic accuracy of cardiologists in predicting LV dysfunction from E...

Unexpected Inequality: Disparate-Impact From Artificial Intelligence in Healthcare Decisions.

Journal of law and health
Systemic discrimination in healthcare plagues marginalized groups. Physicians incorrectly view people of color as having high pain tolerance, leading to undertreatment. Women with disabilities are often undiagnosed because their symptoms are dismisse...

Decision support systems for the prediction of lymph node involvement in early breast cancer.

Journal of B.U.ON. : official journal of the Balkan Union of Oncology
The prediction of lymph node involvement represents an important task which could reduce unnecessary surgery and improve the definition of oncological therapies. An artificial intelligence model able to predict it in pre-operative phase requires the ...

Structuring electronic dental records through deep learning for a clinical decision support system.

Health informatics journal
Extracting information from unstructured clinical text is a fundamental and challenging task in medical informatics. Our study aims to construct a natural language processing (NLP) workflow to extract information from Chinese electronic dental record...

Latent bias and the implementation of artificial intelligence in medicine.

Journal of the American Medical Informatics Association : JAMIA
Increasing recognition of biases in artificial intelligence (AI) algorithms has motivated the quest to build fair models, free of biases. However, building fair models may be only half the challenge. A seemingly fair model could involve, directly or ...

Artificial Intelligence in Quality Improvement: Reviewing Uses of Artificial Intelligence in Noninterpretative Processes from Clinical Decision Support to Education and Feedback.

Journal of the American College of Radiology : JACR
The radiology workflow can be segmented into three large groups: pre-interpretative processes, interpretation, and postinterpretative processes. Each stage of this workflow represents quality improvement opportunities for artificial intelligence and ...

A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To improve patient safety and clinical outcomes by reducing the risk of prescribing errors, we tested the accuracy of a hybrid clinical decision support system in prioritizing prescription checks.