Latest AI and machine learning research in information technology for healthcare professionals.
Digital health technologies, including artificial intelligence, offer immense potential to revolutionise cardiology by improving patient care, enhancing efficiency, and increasing access to specialised services. Benefits may include precision medicine, remote monitoring, streamlined workflows, and accelerated research. However, challenges such as cost, digital literacy, data privacy, interoperabil...
Unsupervised anomaly detection (UAD) in medical imaging is crucial for identifying pathological abnormalities without requiring extensive labeled data. However, existing diffusion-based UAD models rely solely on imaging features, limiting their ability to distinguish between normal anatomical variations and pathological anomalies. To address this, we propose Diff3M, a multi-modal diffusion-based...
Foundation models hold significant promise in healthcare, given their capacity to extract meaningful representations independent of downstream tasks...
Deep learning models trained on extensive Electronic Health Records (EHR) data have achieved high accuracy in diagnosis prediction, offering the pot...
Neuromorphic computing, inspired by the human brain's neural architecture, is revolutionizing artificial intelligence and edge computing with its lo...
In the contemporary digital landscape, cybersecurity has become a critical issue due to the increasing frequency and sophistication of cyber attacks...
Large language models (LLMs) have performed well across various clinical natural language processing tasks, despite not being directly trained on el...
Colorectal cancer remains a major health concern, with colorectal polyps as key precursors. Endoscopic mucosal resection (EMR) is a common treatment, ...
The objective of this study was to develop a machine learning model utilizing data from the electronic health record (EHR) to model length of stay and...
BACKGROUND: Telemedicine, which incorporates artificial intelligence such as chatbots, offers significant potential for enhancing health care delivery...
BACKGROUND: Atrial fibrillation (AF), the most common arrhythmia, is linked to high morbidity and mortality. In a fast-evolving AF rhythm control tr...
The code of nature, embedded in DNA and RNA genomes since the origin of life, holds immense potential to impact both humans and ecosystems through g...
The growing utilization of Internet of Medical Things (IoMT) devices, including smartwatches and wearable medical devices, has facilitated real-time...
Information theory is a powerful framework for quantifying complexity, uncertainty, and dynamical structure in time-series data, with widespread app...
Anomaly detection is a fundamental problem in domains such as healthcare, manufacturing, and cybersecurity. This thesis proposes new unsupervised me...
Concerns regarding privacy and data security in conventional healthcare prompted alternative technologies. In smart healthcare, blockchain technolog...
The rapid advancement of Large Language Models (LLMs) has stimulated interest in multi-agent collaboration for addressing complex medical tasks. How...
Advanced healthcare predictions offer significant improvements in patient outcomes by leveraging predictive analytics. Existing works primarily util...
Automating Electronic Health Records (EHR) documentation can significantly reduce the burden on care providers, particularly in emergency care setting...
Unsupervised anomaly detection is a critical task in many high-social-impact applications such as finance, healthcare, social media, and cybersecuri...