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Information Technology

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

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TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection

Accurate estimation of cancer risk from longitudinal electronic health records (EHRs) could support ...

Identification and Anonymization of Named Entities in Unstructured Information Sources for Use in Social Engineering Detection

This study addresses the challenge of creating datasets for cybercrime analysis while complying with...

GraphWalker: Graph-Guided In-Context Learning for Clinical Reasoning on Electronic Health Records

Clinical Reasoning on Electronic Health Records (EHRs) is a fundamental yet challenging task in mode...

Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clustering

In electronic health records (EHRs), clustering patients and distinguishing disease subtypes are key...

USCNet: Transformer-Based Multimodal Fusion with Segmentation Guidance for Urolithiasis Classification

Kidney stone disease ranks among the most prevalent conditions in urology, and understanding the com...

Are Face Embeddings Compatible Across Deep Neural Network Models?

Automated face recognition has made rapid strides over the past decade due to the unprecedented rise...

Causal Machine Learning for Comparative Effectiveness of GLP-1 RA versus SGLT2i in Heart Failure Using Real-World EHR Data

Clinicians lack precision medicine tools to estimate individualized treatment effects for patients w...

Clinician-Informed Feature Engineering Improves Machine Learning Assignment of Molecular Endotypes in the Intensive Care Unit

Objective: To develop a workflow that transforms electronic health record data into machine learning...

Unlocking Multi-Site Clinical Data: A Federated Approach to Privacy-First Child Autism Behavior Analysis

Automated recognition of autistic behaviors in children is essential for early intervention and obje...

A Tsetlin Machine-driven Intrusion Detection System for Next-Generation IoMT Security

The rapid adoption of the Internet of Medical Things (IoMT) is transforming healthcare by enabling s...

Development and Temporal Evaluation of Multimodal Machine Learning Models to Predict High Inpatient Opioid Exposure

High inpatient opioid exposure is associated with increased risk of persistent opioid use. Early ide...

BSO-AD: An Ontology for Representing and Harmonizing Behavioral Social Knowledge in ADRD

Objective: Behavioral and social factors (BSFs) substantially influence the risk, onset, and progres...

Predicting long-term adverse outcomes after neonatal intensive care

Neonates requiring intensive care are at increased risk for long-term neuropsychiatric disorders. Ho...

Automating Early Disease Prediction Via Structured and Unstructured Clinical Data

This study presents a fully automated methodology for early prediction studies in clinical settings,...

EthoClaw: An Integrated AI Workflow Platform for Automated Analysis in Neuroethology

Computational methods have advanced the analysis of animal behavior, yet significant challenges rema...

HealthFormer: Dual-level time-aware Transformers for irregular electronic health record events

Longitudinal electronic health records (EHRs) form irregular event sequences that mix multiple clini...

S4CMDR: a metadata repository for electronic health records

Background: Electronic health records (EHRs) enable machine learning for diagnosis, prognosis, and c...

Fully Automated Abstraction of Longitudinal Breast Oncology Records with Off-The-Shelf Large Language Models

Background: Manual chart abstraction is a major bottleneck in clinical research. In oncology, import...

S4CMDR: a metadata repository for electronic health records

Background: Electronic health records (EHRs) enable machine learning for diagnosis, prognosis, and c...

Scaling Recurrence-aware Foundation Models for Clinical Records via Next-Visit Prediction

While large-scale pretraining has revolutionized language modeling, its potential remains underexplo...

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