Latest AI and machine learning research in risk management for healthcare professionals.
Since the early 1970s, technology has increasingly become integrated into the healthcare field. Toda...
The intricate and multifaceted nature of vision language model (VLM) development, adaptation, and ...
Despite the widespread adoption of Shannon's confusion-diffusion architecture in image encryption,...
This study introduces PROFIS, a new generative model capable of the design of structurally novel and...
Biological protocols are fundamental to reproducibility and safety in life science research. While...
The prevention and control of emerging and reemerging infectious diseases are crucial for national b...
The purpose of this study was to assess whether a 3-min 2D knee protocol can meet the needs for cli...
Future networks are envisioned to connect massive artificial intelligence (AI) agents, enabling th...
AIMS: Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), pa...
Standardised tests using short answer questions (SAQs) are common in postgraduate education. Large...
Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing m...
The recent proliferation of photorealistic images created by generative models has sparked both ex...
As artificial intelligence systems grow more capable and autonomous, frontier AI development poses...
Automatic anonymization techniques are essential for ethical sharing of pathological speech data, ...
Artificial intelligence (AI) is transforming healthcare by enhancing diagnostics, personalizing medi...
Catalytic constant (Kcat) is to describe the efficiency of catalyzing reactions. The Kcat value of a...
Purpose To assess the effect of scanner manufacturer and scanning protocol on the performance of dee...
To evaluate the clinical performance of a Protocol Recommendation System (PRS) automatic protocolli...
Artificial Intelligence (AI) is a dynamic area of computer science that is constantly expanding its ...
To evaluate the accuracy of a Bidirectional Encoder Representations for Transformers (BERT) Natural...
Purpose To develop and evaluate machine learning and deep learning-based models for automated protoc...