Artificial Intelligence Medical Compendium

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

Showing 14,291 to 14,300 of 211,815 articles

Water-MAS: A multi-agent LLM framework with instruction-data decoupling for smart water management.

Water research
Sustainable water management demands transforming heterogeneous, long-sequence water data into timely, data-driven insights. While single-agent systems can perform basic tasks through tool integration, they suffer from low accuracy, limited adaptabil... read more 

Navigating the "Valley of Death": An Open-Source, Modular Framework for Generative AI in Healthcare.

Studies in health technology and informatics
Generative AI (GenAI) adoption remains limited, particularly in under-resourced settings, despite its many applications. This disparity arises from fragmented integration, privacy concerns, and the translational gap (often called the "Valley of Death... read more 

On the Ethical Aspect of Artificial Intelligence-Based Decision Process for Transplantation.

Studies in health technology and informatics
Liver transplantation is a complex process including organ donors, recipients, as well key stakeholders. We propose a new data workflow able to capture, merge and monitor information regarding several aspects of the transplantation process towards be... read more 

Integration and Harmonization of Multi-Source Obstetric Data Using Rule-Based NLP for Fetomaternal Risk Modelling.

Studies in health technology and informatics
More than 80% of pregnancies in Germany are classified as high risk, leading to inefficient resource allocation. Although data-driven approaches could improve fetomaternal risk prediction, limited standardization across clinical databases remains a m... read more 

Bridging Routine Data and Clinical Research: A Structured Approach to Data Preprocessing.

Studies in health technology and informatics
The secondary use of routine clinical data remains challenging due to heterogeneity and irregularity. We present a structured three-step preprocessing framework to transform routine healthcare data into research-compatible datasets. The approach comp... read more 

Enabling Privacy-Preserving Federated Learning in Healthcare: The FLAME Architecture and Policy Framework.

Studies in health technology and informatics
Federated Learning enables collaborative AI development in healthcare without sharing patient data, addressing privacy and regulatory constraints like GDPR and HIPAA. We present FLAME, an open-source platform developed within the German PrivateAIM pr... read more 

Exploring Documentation Burden and the Use of Artificial Intelligence Among Swiss Rehabilitation Professionals.

Studies in health technology and informatics
This cross-sectional online survey presents preliminary results examining Swiss occupational and physical therapists' (OTs/PTs) documentation burden and attitudes toward artificial intelligence (AI) support. Among 292 respondents (219 PTs, 73 OTs; me... read more 

HeXEHRS: Design and Implementation of a FHIR-Based Cloud EHR and Client for Depopulated Regions with AI and Digital-Twin Integration.

Studies in health technology and informatics
Japan's national initiative for scientific infrastructure emphasizes equitable healthcare delivery in depopulated regions facing rapid aging and physician shortages. To address these challenges, we developed HeXEHRS, a cloud-based electronic health r... read more 

Kernel Density Estimation of Wearable Signals to Predict Preoperative Cancellation Risk.

Studies in health technology and informatics
Digital health approaches that leverage consumer wearables and machine learning offer scalable means to detect acute illness pre-symptomatically, enabling earlier intervention and improved resource planning. Prior studies have shown that wearable-der... read more 

Identification of Reliable Biomarkers for ALS Through Machine Learning Approach.

Studies in health technology and informatics
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive motor neuron degeneration and limited diagnostic biomarkers. Identifying robust molecular biomarkers for ALS remains a major challenge due to disea... read more