Artificial Intelligence Medical Compendium

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

Showing 15,491 to 15,500 of 213,137 articles

Challenges Faced by People with Depression Using AI Chatbots in Saudi Arabia.

Studies in health technology and informatics May 21, 2026
Depression is a common mental health illness that affects hundreds of millions of people worldwide. In Saudi Arabia, depression is considered a major public health concern. Recently, many people have used AI chatbots to seek health information. This ... read more 

Automated Detection of Tuberculosis on Chest X-Rays Using Artificial Intelligence.

Studies in health technology and informatics May 21, 2026
Detecting tuberculosis on X-rays remains complex and challenging for clinicians. In Burkina Faso, the scarcity of radiologists and their heavy workload increase the risk of misinterpretation, particularly in areas with high demand. To address this co... read more 

Semi-Automating Curation of Clinical Practice Guidelines.

Studies in health technology and informatics May 21, 2026
The rapid expansion of clinical knowledge presents significant challenges for maintaining current and comprehensive clinical practice guidelines (CPGs). Manual curation processes are resource-intensive and often result in delayed integration of new e... read more 

Random Forest Model for the Prediction of Herbal-Induced Liver Injury: Application to Molecules from the West African Pharmacopoeia.

Studies in health technology and informatics May 21, 2026
Herbal medicines play a crucial role in primary healthcare across West Africa, yet their potential for liver toxicity remains poorly documented. Predicting herbal-induced liver injury is therefore essential to ensure the safe use of traditional remed... read more 

AI-Based Prediction of Clinical Deterioration in Hospitalised Cardiac Patients.

Studies in health technology and informatics May 21, 2026
INTRODUCTION: The rules based Between the Flags (BTF) system has been the mainstay of early warning of clinical deterioration in public hospitals in New South Wales, Australia. METHODS: A retrospective observational study compared BTF with an artific... read more 

What Is My Data Capable of? Using Performance Limits to Assess Data Quality.

Studies in health technology and informatics May 21, 2026
This study uses information theory to determine theoretical maximum classification performance on 13 healthcare datasets, differentiating between algorithmic limitations and inherent data constraints. Results reveal substantial variability in achieva... read more 

Multimodal Cardiovascular Disease Detection Using ECG Image and EHR.

Studies in health technology and informatics May 21, 2026
ECG is an important signal for cardiovascular disease prediction. Since the ECG signals are often stored as images in clinical practice, we transformed sequential ECG data into images and evaluated the performance of single-modal and multi-modal fusi... read more 

Automatic Placement Within a Hierarchical Clinical Decision Support Terminology.

Studies in health technology and informatics May 21, 2026
Hierarchical terminologies are often used to trigger clinical decision support within electronic health record software systems. This study utilized two algorithms to automate the process of placing clinical terms within a widely used hierarchical de... read more 

A Prediction Model for Cardiovascular Death in Individuals with Prediabetes.

Studies in health technology and informatics May 21, 2026
We developed a machine learning model to estimate the personalized risk of cardiovascular (CV) death within 5-years among obese/overweight people with prediabetes. The model has the potential to enhance early preventive CV strategies. read more 

Deep Learning-Based Prediction of Pathogenicity for ABL1 Protein Variants Using Sequence Representation.

Studies in health technology and informatics May 21, 2026
The ABL1 gene encodes a non-receptor tyrosine kinase implicated in leukemia and other genetic disorders. This study presents a deep learning-based approach for predicting the pathogenicity of ABL1 single amino acid variants (SAVs) using amino acid se... read more 
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