Trialdura: Hierarchical attention transformer for interpretable clinical trial duration prediction
The clinical trial process, a critical phase in drug development, is essential for developing
new treatments. The primary goal of interventional clinical trials is to evaluate the safety and …
new treatments. The primary goal of interventional clinical trials is to evaluate the safety and …
Clinicalagent: Clinical trial multi-agent system with large language model-based reasoning
Large Language Models (LLMs) and multi-agent systems have shown impressive
capabilities in natural language tasks but face challenges in clinical trial applications …
capabilities in natural language tasks but face challenges in clinical trial applications …
DeepProtein: Deep Learning Library and Benchmark for Protein Sequence Learning
In recent years, deep learning has revolutionized the field of protein science, enabling
advancements in predicting protein properties, structural folding and interactions. This paper …
advancements in predicting protein properties, structural folding and interactions. This paper …
Protein-Mamba: Biological Mamba Models for Protein Function Prediction
Protein function prediction is a pivotal task in drug discovery, significantly impacting the
development of effective and safe therapeutics. Traditional machine learning models often …
development of effective and safe therapeutics. Traditional machine learning models often …
Accelerated Markov Chain Monte Carlo Using Adaptive Weighting Scheme
Y Wang, W Chen, S Shan - arXiv preprint arXiv:2408.12888, 2024 - arxiv.org
Gibbs sampling is one of the most commonly used Markov Chain Monte Carlo (MCMC)
algorithms due to its simplicity and efficiency. It cycles through the latent variables, sampling …
algorithms due to its simplicity and efficiency. It cycles through the latent variables, sampling …