BACKGROUND: Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT (OpenAI), is rapidly influencing medical education. Its effectiveness for students with varying levels of prior knowledge remains underexplored.
Physics-Informed Kolmogorov-Arnold Networks (PIKANs) have been gaining attention as an effective counterpart to the original multilayer perceptron-based Physics-Informed Neural Networks (PINNs). Both representation models can address inverse problems...
BACKGROUND: The rapid rise of AI in medical and pharmaceutical education has engendered much interest; however, a knowledge gap still exists in the evaluation of performances of these tools in critical academic contexts.
BACKGROUND: With the growing integration of artificial intelligence in medical education, this study compares the quality and educational robustness of content generated by two large language models (LLMs), DeepSeek-V3 and ChatGPT 4.0, on the emergin...
One of the identified points of confusion and a barrier to students using generative artificial intelligence (GenAI) is knowing what their professor would consider appropriate use of GenAI in a classroom setting or course framework. This creates poin...
BACKGROUND: Medical students often struggle to engage with and retain complex pharmacology topics during their preclinical education. Traditional teaching methods can lead to passive learning and poor long-term retention of critical concepts.
Deep learning neural networks are often described as black boxes, as it is difficult to trace model outputs back to model inputs due to a lack of clarity over the internal mechanisms. This is even true for those neural networks designed to emulate me...
Over the past few decades, the number of health and 'omics-related data' generated and stored has grown exponentially. Patient information can be collected in real time and explored using various artificial intelligence (AI) tools in clinical trials;...
CPT: pharmacometrics & systems pharmacology
May 2, 2021
Although there is increased interest in utilizing machine learning (ML) to support drug development, technical hurdles associated with complex algorithms have limited widespread adoption. In response, we have developed Pharm-AutoML, an open-source Py...
INTRODUCTION: The SARS-CoV-2 pandemic has led to one of the most critical and boundless waves of publications in the history of modern science. The necessity to find and pursue relevant information and quantify its quality is broadly acknowledged. Mo...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.