Information Technology

A GEN AI Framework for Medical Note Generation

The increasing administrative burden of medical documentation, particularly through Electronic Health Records (EHR), significantly reduces the time available for direct patient care and contributes to physician burnout. To address this issue, we propose MediNotes, an advanced generative AI framework designed to automate the creation of SOAP (Subjective, Objective, Assessment, Plan) notes from me...

Suicide Phenotyping from Clinical Notes in Safety-Net Psychiatric Hospital Using Multi-Label Classification with Pre-Trained Language Models

Accurate identification and categorization of suicidal events can yield better suicide precautions, reducing operational burden, and improving care quality in high-acuity psychiatric settings. Pre-trained language models offer promise for identifying suicidality from unstructured clinical narratives. We evaluated the performance of four BERT-based models using two fine-tuning strategies (multipl...

Adversarial Challenges in Network Intrusion Detection Systems: Research Insights and Future Prospects

Machine learning has brought significant advances in cybersecurity, particularly in the development of Intrusion Detection Systems (IDS). These impr...

Retrospective Comparative Analysis of Prostate Cancer In-Basket Messages: Responses from Closed-Domain LLM vs. Clinical Teams

In-basket message interactions play a crucial role in physician-patient communication, occurring during all phases (pre-, during, and post) of a pat...

Towards Forever Access for Implanted Brain-Computer Interfaces

Designs for implanted brain-computer interfaces (BCIs) have increased significantly in recent years. Each device promises better clinical outcomes a...

KIPPS: Knowledge infusion in Privacy Preserving Synthetic Data Generation

The integration of privacy measures, including differential privacy techniques, ensures a provable privacy guarantee for the synthetic data. However...

Building a Natural Language Interface for FHIR Clinical Terminology Server.

While Fast Healthcare Interoperability Resources (FHIR) clinical terminology server enables quick and easy search and retrieval of coded medical data,...

OSINT Clinic: Co-designing AI-Augmented Collaborative OSINT Investigations for Vulnerability Assessment

Small businesses need vulnerability assessments to identify and mitigate cyber risks. Cybersecurity clinics provide a solution by offering students ...

Payments Use Cases and Design Options for Interoperability and Funds Locking across Digital Pounds and Commercial Bank Money

Central banks are actively exploring retail central bank digital currencies (CBDCs), with the Bank of England currently in the design phase for a po...

SoK: Security and Privacy Risks of Healthcare AI

The integration of artificial intelligence (AI) and machine learning (ML) into healthcare systems holds great promise for enhancing patient care and...

Classification performance and reproducibility of GPT-4 omni for information extraction from veterinary electronic health records

Large language models (LLMs) can extract information from veterinary electronic health records (EHRs), but performance differences between models, t...

Clinical risk prediction using language models: benefits and considerations.

OBJECTIVE: The use of electronic health records (EHRs) for clinical risk prediction is on the rise. However, in many practical settings, the limited a...

Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings.

OBJECTIVES: To evaluate the proficiency of a HIPAA-compliant version of GPT-4 in identifying actionable, incidental findings from unstructured radiolo...

Branch-and-cut algorithms for colorful components problems

We tackle three optimization problems in which a colored graph, where each node is assigned a color, must be partitioned into colorful connected com...

Knowledge Base Prototype Creating with Using Interdisciplinary Metathesaurus.

This article presents our experience in development an ontological model can be used in clinical decision support systems (CDSS) creating. We have use...

Harnessing the Power of Machine Learning and Electronic Health Records to Support Child Abuse and Neglect Identification in Emergency Department Settings.

Emergency departments (EDs) are pivotal in detecting child abuse and neglect, but this task is often complex. Our study developed a machine learning m...

Active Learning Pipeline to Identify Candidate Terms for a CDSS Ontology.

Ontology is essential for achieving health information and information technology application interoperability in the biomedical fields and beyond. Tr...

How Interoperability Can Enable Artificial Intelligence in Clinical Applications.

This paper explores the critical role of Interoperability (IOP) in the integration of Artificial Intelligence (AI) for clinical applications. As AI ga...

Secure Extraction of Personal Information from EHR by Federated Machine Learning.

Secure extraction of Personally Identifiable Information (PII) from Electronic Health Records (EHRs) presents significant privacy and security challen...

A Concept for Integrating AI-Based Support Systems into Clinical Practice.

The integration of artificial intelligence (AI) algorithms into clinical practice holds immense potential to improve patient care, but widespread adop...