Information Technology

MKE-Coder: Multi-Axial Knowledge with Evidence Verification in ICD Coding for Chinese EMRs

The task of automatically coding the International Classification of Diseases (ICD) in the medical field has been well-established and has received much attention. Automatic coding of the ICD in the medical field has been successful in English but faces challenges when dealing with Chinese electronic medical records (EMRs). The first issue lies in the difficulty of extracting disease code-relate...

Domination in Graph Theory: A Bibliometric Analysis of Research Trends, Collaboration and Citation Networks

This study conducts a comprehensive bibliometric analysis of research on domination in graph theory from 1961 to 2024, based on Scopus-indexed publications retrieved using the query (dominating OR domination) AND graph. The analysis examines publication trends, key contributors, collaboration patterns, citation impact, and emerging research themes. Results indicate a significant and sustained in...

A Guide for Implementing an A.I-Driven Initiative in Rural Northern Ontario.

Diagnosing pulmonary embolism (PE) often requires specialized expertise in interpreting x-rays and radiographic images, resources that are mostly limi...

Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset

The rapid proliferation of Internet of Medical Things (IoMT) devices in healthcare has introduced unique cybersecurity challenges, primarily due to ...

Towards a Trustworthy Anomaly Detection for Critical Applications through Approximated Partial AUC Loss

Anomaly Detection is a crucial step for critical applications such in the industrial, medical or cybersecurity domains. These sectors share the same...

Primus: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Training

Large Language Models (LLMs) have shown remarkable advancements in specialized fields such as finance, law, and medicine. However, in cybersecurity,...

Leveraging Large Language Models for Cybersecurity: Enhancing SMS Spam Detection with Robust and Context-Aware Text Classification

This study evaluates the effectiveness of different feature extraction techniques and classification algorithms in detecting spam messages within SM...

MITRE ATT&CK Applications in Cybersecurity and The Way Forward

The MITRE ATT&CK framework is a widely adopted tool for enhancing cybersecurity, supporting threat intelligence, incident response, attack modeling,...

Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction

The burgeoning volume of electronic health records (EHRs) has enabled deep learning models to excel in predictive healthcare. However, for high-stak...

Leveraging large language models for structured information extraction from pathology reports

Background: Structured information extraction from unstructured histopathology reports facilitates data accessibility for clinical research. Manual ...

A Roadmap to Address Burnout in the Cybersecurity Profession: Outcomes from a Multifaceted Workshop

This paper addresses the critical issue of burnout among cybersecurity professionals, a growing concern that threatens the effectiveness of digital ...

Decentralized Entropy-Based Ransomware Detection Using Autonomous Feature Resonance

The increasing sophistication of cyber threats has necessitated the development of advanced detection mechanisms capable of identifying malicious ac...

Medical Applications of Graph Convolutional Networks Using Electronic Health Records: A Survey

Graph Convolutional Networks (GCNs) have emerged as a promising approach to machine learning on Electronic Health Records (EHRs). By constructing a ...

Representation Learning to Advance Multi-institutional Studies with Electronic Health Record Data

The adoption of EHRs has expanded opportunities to leverage data-driven algorithms in clinical care and research. A major bottleneck in effectively ...

Decentralized Entropy-Driven Ransomware Detection Using Autonomous Neural Graph Embeddings

The increasing sophistication of cyber threats has necessitated the development of advanced detection mechanisms capable of identifying and mitigati...

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization

Attributing APT (Advanced Persistent Threat) malware to their respective groups is crucial for threat intelligence and cybersecurity. However, APT a...

Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer

Early prediction of pediatric cardiac arrest (CA) is critical for timely intervention in high-risk intensive care settings. We introduce PedCA-FT, a...

CliniQ: A Multi-faceted Benchmark for Electronic Health Record Retrieval with Semantic Match Assessment

Electronic Health Record (EHR) retrieval plays a pivotal role in various clinical tasks, but its development has been severely impeded by the lack o...

ELMTEX: Fine-Tuning Large Language Models for Structured Clinical Information Extraction. A Case Study on Clinical Reports

Europe's healthcare systems require enhanced interoperability and digitalization, driving a demand for innovative solutions to process legacy clinic...

AI-Driven Electronic Health Records System for Enhancing Patient Data Management and Diagnostic Support in Egypt

Digital healthcare infrastructure is crucial for global medical service delivery. Egypt faces EHR adoption barriers: only 314 hospitals had such sys...