AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Decision Support Systems, Clinical

Showing 551 to 560 of 696 articles

Clear Filters

Improving the delivery of palliative care through predictive modeling and healthcare informatics.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, many patients who could benefit from PC do not receive it early enough or at all. We sought to address...

Machine-learning model to predict the cause of death using a stacking ensemble method for observational data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Cause of death is used as an important outcome of clinical research; however, access to cause-of-death data is limited. This study aimed to develop and validate a machine-learning model that predicts the cause of death from the patient's l...

Towards a Knowledge Graph-Based Explainable Decision Support System in Healthcare.

Studies in health technology and informatics
The decisions derived from AI-based clinical decision support systems should be explainable and transparent so that the healthcare professionals can understand the rationale behind the predictions. To improve the explanations, knowledge graphs are a ...

Recommendations for the safe, effective use of adaptive CDS in the US healthcare system: an AMIA position paper.

Journal of the American Medical Informatics Association : JAMIA
The development and implementation of clinical decision support (CDS) that trains itself and adapts its algorithms based on new data-here referred to as Adaptive CDS-present unique challenges and considerations. Although Adaptive CDS represents an ex...

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...