Artificial Intelligence Medical Compendium

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

Showing 13,831 to 13,840 of 211,462 articles

Evaluating the Potential of Machine Learning for Discharge Management on Routine Health Insurance Data.

Studies in health technology and informatics
Machine learning (ML) has great potential in healthcare, especially with large structured data. Routine health insurance claims (HIC) data are a valuable resource, comprising standardized longitudinal patient information. However, to fully leverage M... read more 

Identification of Cervical Cancer Biomarkers Using Gene Co-Expression Networks and Machine Learning Methods.

Studies in health technology and informatics
Cervical cancer (CC) causes significant mortality due to late diagnosis and limited understanding of its molecular drivers. The complex gene co-expression patterns associated with CC remain poorly characterized. Identifying key genes that distinguish... read more 

Neurologists' Expectations of AI in Clinical Practice: A Study on Task Prioritisation and Patient-Centred Perspectives.

Studies in health technology and informatics
As part of the digital health transformation, artificial intelligence (AI) is reshaping patient-centred care by merging technological innovation with value-driven healthcare, particularly in chronic disease management, where long-term care continuity... read more 

Machine Learning Models for Predicting Mortality Risk and Survival Time in Lung Cancer Patients Treated with EGFR-TKIs.

Studies in health technology and informatics
This study develops machine learning models to predict patient mortality and estimate survival time using electronic health record (EHR) data from three Taipei Medical University-affiliated hospitals (TMU Hospital, Wan-Fang Hospital, and Shuang Ho Ho... read more 

Machine Learning Prediction of Growth Hormone Response in Children Non-Growth Hormone-Deficient Short Stature.

Studies in health technology and informatics
Height gain under recombinant human growth hormone (rhGH) varies widely in children with short stature, making early, reliable response prediction essential for individualized care. Using routinely collected data from Bambino Gesù Children's Hospital... read more 

Knowledge-Based Interpretation of Multi-Modal Clinical Findings: Evaluating a Local Agentic Bridge Between Worlds.

Studies in health technology and informatics
Contemporary clinical practice still produces unstructured data like free-text reports or scans, hindering automated interpretation by knowledge-based clinical decision support (CDS) systems that rely on structured data. Large language models (LLMs) ... read more 

Explainable Framework for Ontology-Based Similarity: A Use Case on SNOMED CT.

Studies in health technology and informatics
In healthcare, being able to efficiently manipulate and compare concepts in ontologies is crucial to enable semantic interoperability of clinical data. Most ontology-based similarity functions return a single score with little actionable justificatio... read more 

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

Studies in health technology and informatics
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
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
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