Latest AI and machine learning research in information technology for healthcare professionals.
We developed and validated TRisk, a Transformer-based AI model predicting 36-month mortality in heart failure patients by analysing temporal patient journeys from UK electronic health records (EHR). Our study included 403,534 heart failure patients (ages 40-90) from 1,418 English general practices, with 1,063 practices for model derivation and 355 for external validation. TRisk was compared agai...
Entity Segmentation (ES) aims at identifying and segmenting distinct entities within an image without the need for predefined class labels. This characteristic makes ES well-suited to open-world applications with adaptation to diverse and dynamically changing environments, where new and previously unseen entities may appear frequently. Existing ES methods either require large annotated datasets ...
Background: Social determinants of health (SDoH) play a crucial role in influencing health outcomes, accounting for nearly 50% of modifiable health ...
Despite promising performance on open-source large vision-language models (LVLMs), transfer-based targeted attacks often fail against black-box comm...
Data-driven AI is establishing itself at the center of evidence-based medicine. However, reports of shortcomings and unexpected behavior are growing...
Introduction: Timely care in a specialised neuro-intensive therapy unit (ITU) reduces mortality and hospital stays, with planned admissions being sa...
This paper investigates the critical issue of data poisoning attacks on AI models, a growing concern in the ever-evolving landscape of artificial in...
The Antibiotic Resistance Microbiology Dataset (ARMD) is a de-identified resource derived from electronic health records (EHR) that facilitates rese...
Longitudinal data in electronic health records (EHRs) represent an individual`s clinical history through a sequence of codified concepts, including ...
Large language models (LLMs) have emerged as promising tools for assisting in medical tasks, yet processing Electronic Health Records (EHRs) present...
Generative AI promises to finally realize dynamic, personalized storytelling technologies across a range of media. To date, experimentation with gen...
The increasing adoption of Electric Vehicles (EVs) and the expansion of charging infrastructure and their reliance on communication expose Electric ...
Children with neurodevelopmental disorders require timely intervention to improve long-term outcomes, yet early screening remains inaccessible in ma...
Machine learning has become a key tool in cybersecurity, improving both attack strategies and defense mechanisms. Deep learning models, particularly...
The electronic health record (EHR) contains valuable patient data and offers opportunities to administer and analyse patients' individual needs longit...
Recent advances have given rise to a spectrum of digital health technologies that have the potential to revolutionize the design and conduct of cardio...
Clinical trial eligibility matching is a critical yet often labor-intensive and error-prone step in medical research, as it ensures that participant...
Integrating blockchain technology into healthcare systems presents a transformative approach to documenting, storing, and accessing electronic healt...
BACKGROUND: Generative AI, particularly large language models (LLMs), holds great potential for improving patient care and operational efficiency in h...
This study investigates the feasibility of automating clinical coding in Russian, a language with limited biomedical resources. We present a new dat...