AIMC Topic: Decision Support Systems, Clinical

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Clinicians and AI use: where is the professional guidance?

Journal of medical ethics
With the introduction of artificial intelligence (AI) to healthcare, there is also a need for professional guidance to support its use. New (2022) reports from National Health Service AI Lab & Health Education England focus on healthcare workers' und...

Assessing the Utility, Impact, and Adoption Challenges of an Artificial Intelligence-Enabled Prescription Advisory Tool for Type 2 Diabetes Management: Qualitative Study.

JMIR human factors
BACKGROUND: The clinical management of type 2 diabetes mellitus (T2DM) presents a significant challenge due to the constantly evolving clinical practice guidelines and growing array of drug classes available. Evidence suggests that artificial intelli...

Enhancing Clinical Decision Support in Nephrology: Addressing Algorithmic Bias Through Artificial Intelligence Governance.

American journal of kidney diseases : the official journal of the National Kidney Foundation
There has been a steady rise in the use of clinical decision support (CDS) tools to guide nephrology as well as general clinical care. Through guidance set by federal agencies and concerns raised by clinical investigators, there has been an equal ris...

Predicting ICU Interventions: A Transparent Decision Support Model Based on Multivariate Time Series Graph Convolutional Neural Network.

IEEE journal of biomedical and health informatics
In this study, we present a novel approach for predicting interventions for patients in the intensive care unit using a multivariate time series graph convolutional neural network. Our method addresses two critical challenges: the need for timely and...

A computational clinical decision-supporting system to suggest effective anti-epileptic drugs for pediatric epilepsy patients based on deep learning models using patient's medical history.

BMC medical informatics and decision making
BACKGROUND: Epilepsy, a chronic brain disorder characterized by abnormal brain activity that causes seizures and other symptoms, is typically treated using anti-epileptic drugs (AEDs) as the first-line therapy. However, due to the variations in their...

Achieving large-scale clinician adoption of AI-enabled decision support.

BMJ health & care informatics
Computerised decision support (CDS) tools enabled by artificial intelligence (AI) seek to enhance accuracy and efficiency of clinician decision-making at the point of care. Statistical models developed using machine learning (ML) underpin most curren...

Evaluation of an automated clinical decision system with deep learning dose prediction and NTCP model for prostate cancer proton therapy.

Physics in medicine and biology
To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model.Two 3D UNets were established to predict ph...

The Effect of Artificial Intelligence on Patient-Physician Trust: Cross-Sectional Vignette Study.

Journal of medical Internet research
BACKGROUND: Clinical decision support systems (CDSSs) based on routine care data, using artificial intelligence (AI), are increasingly being developed. Previous studies focused largely on the technical aspects of using AI, but the acceptability of th...

Artificial intelligence model for tumoral clinical decision support systems.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Comparative diagnostic in brain tumor evaluation makes possible to use the available information of a medical center to compare similar cases when a new patient is evaluated. By leveraging Artificial Intelligence models, the...

Mobile Diagnostic Clinics.

ACS sensors
This article reviews the revolutionary impact of emerging technologies and artificial intelligence (AI) in reshaping modern healthcare systems, with a particular focus on the implementation of mobile diagnostic clinics. It presents an insightful anal...