Information Technology

SemOntoMap: A Hybrid Approach for Semantic Annotation of Clinical Texts.

This study addresses the challenge of leveraging free-text descriptions in Electronic Health Records (EHR) for clinical research and healthcare improvement. Despite the potential of this data, its direct interpretation by computers is limited. Semantic annotation emerges as a method to make EHR free text machine-interpretable but struggles with specific domain ontologies and faces heightened diffi...

Unlocking the Potential of Free Text in Electronic Health Records with Large Language Models (LLM): Enhancing Patient Safety and Consultation Interactions.

Computer-mediated clinical consultation, involving clinicians, electronic health record (EHR) systems, and patients, yield rich narrative data. Despite advancements in Natural Language Processing (NLP), these narratives remain underutilised. Free text recording in EHRs allows expressivity, complements structured data from clinical coding systems, and facilitates collaborative care. Large language ...

From EHR to Machine Learning: A Preliminary Report on an Ingestion Pipeline Based on JSON-LD.

In this paper, we present the preliminary experiments for the development of an ingestion mechanism to move data from Electronic Health Records to mac...

Design of a Digital Twin of the Heart for the Management of Heart Failure Patients.

Heart failure poses a significant global health burden with high prevalence and mortality rates. A promising possibility in this context is the consta...

A Comprehensive Natural Language Processing Pipeline for the Chronic Lupus Disease.

Electronic Health Records (EHRs) contain a wealth of unstructured patient data, making it challenging for physicians to do informed decisions. In this...

Evaluation of Machine Learning Algorithms for Pressure Injury Risk Assessment in a Hospital with Limited IT Resources.

Clinical decision support systems for Nursing Process (NP-CDSSs) help resolve a critical challenge in nursing decision-making through automating the N...

In-Memory Computing Architecture for Efficient Hardware Security

This paper presents an innovative approach utilizing in-memory computing (IMC) for the development and integration of AES (Advanced Encryption Stand...

Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory

Privacy research has attracted wide attention as individuals worry that their private data can be easily leaked during interactions with smart devic...

Extending Network Intrusion Detection with Enhanced Particle Swarm Optimization Techniques

The present research investigates how to improve Network Intrusion Detection Systems (NIDS) by combining Machine Learning (ML) and Deep Learning (DL...

A Structural Feature-Based Approach for Comprehensive Graph Classification

The increasing prevalence of graph-structured data across various domains has intensified greater interest in graph classification tasks. While nume...

AI-Driven Chatbot for Intrusion Detection in Edge Networks: Enhancing Cybersecurity with Ethical User Consent

In today's contemporary digital landscape, chatbots have become indispensable tools across various sectors, streamlining customer service, providing...

Cumulus: a federated electronic health record-based learning system powered by Fast Healthcare Interoperability Resources and artificial intelligence.

OBJECTIVE: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, c...

Stratifying heart failure patients with graph neural network and transformer using Electronic Health Records to optimize drug response prediction.

OBJECTIVES: Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for health...

Natural Language Processing Accurately Differentiates Cancer Symptom Information in Electronic Health Record Narratives.

PURPOSE: Identifying cancer symptoms in electronic health record (EHR) narratives is feasible with natural language processing (NLP). However, more ef...

Ontologies related to livestock for the Global Burden of Animal Diseases programme: a review.

The Global Burden of Animal Diseases (GBADs) programme aims to assess the impact of animal health on agricultural animals, livestock production system...

Covering a Graph with Dense Subgraph Families, via Triangle-Rich Sets

Graphs are a fundamental data structure used to represent relationships in domains as diverse as the social sciences, bioinformatics, cybersecurity,...

Blockchain in Healthcare: Implementing Hyperledger Fabric for Electronic Health Records at Frere Provincial Hospital

As healthcare systems worldwide continue to grapple with the challenges of interoperability, data security, and accessibility, integrating emerging ...

CVE-LLM : Automatic vulnerability evaluation in medical device industry using large language models

The healthcare industry is currently experiencing an unprecedented wave of cybersecurity attacks, impacting millions of individuals. With the discov...

Next-Generation 6G Networks: Deploying Cybertwin Technology for Enhanced Healthcare Solutions

This paper explores the integration of Cybertwin technology within 6G networks to revolutionize healthcare delivery. It aims to enhance real-time mo...

[The innovation and challenge of artificial intelligence in the whole process management of fundus disease].

Artificial intelligence (AI) has demonstrated revolutionary potential and wide-ranging applications in the comprehensive management of fundus diseases...