AI Medical Compendium Topic

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Decision Support Systems, Clinical

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Developing an AI-Assisted Platform to Support Tuberculosis Care Delivery.

Studies in health technology and informatics
Artificial Intelligence (AI) has the potential to "bridge the gap" between healthcare provider and patient needs in low-resource settings to deliver timely, personalized, and empathetic care to individuals with active tuberculosis.

Application of Artificial Intelligence in Clinical Practice - Perception of a Multinational Group of Nephrologists.

Studies in health technology and informatics
This study investigates the perception of a multinational group of nephrologists on artificial intelligence (AI) application in clinical practice. A validated on-line survey was performed in March 2024, in 4 continents. The results revealed a prevale...

Multi-Objective Performance Optimization of Machine Learning Models in Healthcare.

Studies in health technology and informatics
Multi-objective optimization holds particular significance for medical applications, wherein enhancing sensitivity is crucial to avoid costly missed diagnoses, and maintaining high specificity is imperative to prevent unnecessary procedures. In parti...

How Trueness of Clinical Decision Support Systems Based on Machine Learning Is Assessed?

Studies in health technology and informatics
The application of machine learning algorithms in clinical decision support systems (CDSS) holds great promise for advancing patient care, yet practical implementation faces significant evaluation challenges. Through a scoping review, we investigate ...

Leveraging Rule-Based NLP to Translate Textual Reports as Structured Inputs Automatically Processed by a Clinical Decision Support System.

Studies in health technology and informatics
Using clinical decision support systems (CDSSs) for breast cancer management necessitates to extract relevant patient data from textual reports which is a complex task although efficiently achieved by machine learning but black box methods. We propos...

A Concept for Integrating AI-Based Support Systems into Clinical Practice.

Studies in health technology and informatics
The integration of artificial intelligence (AI) algorithms into clinical practice holds immense potential to improve patient care, but widespread adoption still faces significant challenges, including interoperability issues. We propose a concept for...

User-Centered Development of Explanation User Interfaces for AI-Based CDSS: Lessons Learned from Early Phases.

Studies in health technology and informatics
This paper reports lessons learned during the early phases of the user-centered design process for an explanation user interface for an AI-based clinical decision support system for the intensive care unit. This paper focuses on identifying and verif...

Challenges and Opportunities of Artificial Intelligence in CDSS and Patient Safety.

Studies in health technology and informatics
Ensuring patient safety in healthcare involves training professionals and implementing clinical decision support systems (CDSS) and health IT solutions to reduce errors and adverse events. The integration of artificial intelligence (AI) into health I...

INSAFEDARE Project: Innovative Applications of Assessment and Assurance of Data and Synthetic Data for Regulatory Decision Support.

Studies in health technology and informatics
Digital health solutions hold promise for enhancing healthcare delivery and patient outcomes, primarily driven by advancements such as machine learning, artificial intelligence, and data science, which enable the development of integrated care system...

Applying Machine Learning for Prescriptive Support: A Use Case with Unfractionated Heparin in Intensive Care Units.

Studies in health technology and informatics
Continuous unfractionated heparin is widely used in intensive care, yet its complex pharmacokinetic properties complicate the determination of appropriate doses. To address this challenge, we developed machine learning models to predict over- and und...