Practice Management

Information Technology

Latest AI and machine learning research in information technology for healthcare professionals.

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Showing 2080-2100 of 4,576 articles
Uncovering Important Diagnostic Features for Alzheimer's, Parkinson's and Other Dementias Using Interpretable Association Mining Methods.

Alzheimer's Disease and Related Dementias (ADRD) afflict almost 7 million people in the USA alone. T...

Jan 2025 39670401
A Dynamic Model for Early Prediction of Alzheimer's Disease by Leveraging Graph Convolutional Networks and Tensor Algebra.

Alzheimer's disease (AD) is a neurocognitive disorder that deteriorates memory and impairs cognitive...

Jan 2025 39670404
Researching public health datasets in the era of deep learning: a systematic literature review.

Explore deep learning applications in predictive analytics for public health data, identify challen...

Jan 2025 39794941
Artificial Intelligence-Assisted Matching of Human Postmortem Donors to Ocular Research Projects.

The scarcity of human ocular samples with short postmortem intervals (PMIs) is a significant issue i...

Jan 2025 39930245
Digital transformation in healthcare management: from Artificial Intelligence to blockchain.

The digital transformation of healthcare is revolutionizing the management of medical institutions, ...

Jan 2025 40219885
HCAP: Hybrid cyber attack prediction model for securing healthcare applications.

The rapid development and integration of interconnected healthcare devices and communication network...

Jan 2025 40354442
SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction

Sepsis is an organ dysfunction caused by a deregulated immune response to an infection. Early seps...

The Future of IPTV: Security, AI Integration, 5G, and Next-Gen Streaming

The evolution of Internet Protocol Television (IPTV) has transformed the landscape of digital broa...

SurvAttack: Black-Box Attack On Survival Models through Ontology-Informed EHR Perturbation

Survival analysis (SA) models have been widely studied in mining electronic health records (EHRs),...

scReader: Prompting Large Language Models to Interpret scRNA-seq Data

Large language models (LLMs) have demonstrated remarkable advancements, primarily due to their cap...

A Machine Learning Approach for Emergency Detection in Medical Scenarios Using Large Language Models

The rapid identification of medical emergencies through digital communication channels remains a c...

Transversal PACS Browser API: Addressing Interoperability Challenges in Medical Imaging Systems

Advances in imaging technologies have revolutionised the medical imaging and healthcare sectors, l...

PT: A Plain Transformer is Good Hospital Readmission Predictor

Hospital readmission prediction is critical for clinical decision support, aiming to identify pati...

BioBridge: Unified Bio-Embedding with Bridging Modality in Code-Switched EMR

Pediatric Emergency Department (PED) overcrowding presents a significant global challenge, prompti...

An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk Estimation

Reliable prediction of pediatric obesity can offer a valuable resource to providers, helping them ...

CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care Data Interoperability

The rise of digital platforms has led to an increasing reliance on technology-driven, home-based h...

Predicting Emergency Department Visits for Patients with Type II Diabetes

Over 30 million Americans are affected by Type II diabetes (T2D), a treatable condition with signi...

Combining knowledge graphs and LLMs for hazardous chemical information management and reuse

Human health is increasingly threatened by exposure to hazardous substances, particularly persiste...

Access to care improves EHR reliability and clinical risk prediction model performance

Disparities in access to healthcare have been well-documented in the United States, but their effe...

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs

Foundation Models (FMs) trained on Electronic Health Records (EHRs) have achieved state-of-the-art...

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