Latest AI and machine learning research in risk management for healthcare professionals.
Large Language Models (LLMs) are increasingly integrated into critical systems in industries like healthcare and finance. Users can often submit queries to LLM-enabled chatbots, some of which can enrich responses with information retrieved from internal databases storing sensitive data. This gives rise to a range of attacks in which a user submits a malicious query and the LLM-system outputs a r...
Suicide remains one of the main preventable causes of death among active service members and veterans. Early detection and prediction are crucial in suicide prevention. Machine learning techniques have yielded promising results in this area recently. This study aims to assess and summarize current research and provides a comprehensive review regarding the application of machine learning techniqu...
Large language models (LLMs) are increasingly deployed in medical contexts, raising critical concerns about safety, alignment, and susceptibility to...
Clinical trials are vital for evaluation of safety and efficacy of new treatments. However, clinical trials are resource-intensive, time-consuming a...
INTRODUCTION: Deep brain stimulation (DBS) is a proven effective treatment for Parkinson's disease (PD). However, titrating DBS stimulation parameters...
The proliferation of AI agents requires robust mechanisms for secure discovery. This paper introduces the Agent Name Service (ANS), a novel architec...
Explainable Artificial Intelligence (XAI) is crucial for enhancing transparency, interpretability and actionability of AI systems, particularly in hea...
Pacing is a key mechanism in modern transport protocols, used to regulate packet transmission timing to minimize traffic burstiness, lower latency, ...
The process of linking databases that contain sensitive information about individuals across organisations is an increasingly common requirement in ...
Since the early 1970s, technology has increasingly become integrated into the healthcare field. Today, artificial intelligence (AI) and machine learni...
The intricate and multifaceted nature of vision language model (VLM) development, adaptation, and application necessitates the establishment of clea...
Despite the widespread adoption of Shannon's confusion-diffusion architecture in image encryption, the implementation of diffusion to sequentially e...
This study introduces PROFIS, a new generative model capable of the design of structurally novel and target-focused compound libraries. The model reli...
Biological protocols are fundamental to reproducibility and safety in life science research. While large language models (LLMs) perform well on gene...
The prevention and control of emerging and reemerging infectious diseases are crucial for national biosecurity, and surveillance and reporting of pneu...
The purpose of this study was to assess whether a 3-min 2D knee protocol can meet the needs for clinical application if using a SuperResolution recon...
Future networks are envisioned to connect massive artificial intelligence (AI) agents, enabling their extensive collaboration on diverse tasks. Comp...
AIMS: Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural opt...
Standardised tests using short answer questions (SAQs) are common in postgraduate education. Large language models (LLMs) simulate conversational la...
Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models still struggle with prompts that require ric...