1 citations · 1 across the 3 of their papers we have counts for
5 papers
BioDSA-1K: Benchmarking Data Science Agents for Biomedical Research
Zifeng Wang, Benjamin Danek, Jimeng Sun
Validating scientific hypotheses is a central challenge in biomedical research, and remains difficult for artificial intelligence (AI) agents due to the complexity of real-world da…
Developing Large Language Models for Clinical Research Using One Million Clinical Trials
Zifeng Wang, Jiacheng Lin, Qiao Jin +5
Developing artificial intelligence (AI) for clinical research requires a comprehensive data foundation that supports model training and rigorous evaluation. Here, we introduce Tria…
InformGen: An AI Copilot for Accurate and Compliant Clinical Research Consent Document Generation
Zifeng Wang, Junyi Gao, Benjamin Danek +5
Leveraging large language models (LLMs) to generate high-stakes documents, such as informed consent forms (ICFs), remains a significant challenge due to the extreme need for regula…
A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges
Zifeng Wang, Hanyin Wang, Benjamin Danek +6
The integration of Large Language Models (LLMs) into medical applications has sparked widespread interest across the healthcare industry, from drug discovery and development to cli…
Can Large Language Models Replace Data Scientists in Biomedical Research?
Zifeng Wang, Benjamin Danek, Ziwei Yang +2
Data science plays a critical role in biomedical research, but it requires professionals with expertise in coding and medical data analysis. Large language models (LLMs) have shown…