Session Introduction: Artificial Intelligence in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface.

Journal: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Published Date: Jan 1, 2024

Abstract

Artificial Intelligence (AI) models are substantially enhancing the capability to analyze complex and multi-dimensional datasets. Generative AI and deep learning models have demonstrated significant advancements in extracting knowledge from unstructured text, imaging as well as structured and tabular data. This recent breakthrough in AI has inspired research in medicine, leading to the development of numerous tools for creating clinical decision support systems, monitoring tools, image interpretation, and triaging capabilities. Nevertheless, comprehensive research is imperative to evaluate the potential impact and implications of AI systems in healthcare. At the 2024 Pacific Symposium on Biocomputing (PSB) session entitled "Artificial Intelligence in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface", we spotlight research that develops and applies AI algorithms to solve real-world problems in healthcare.

Authors

  • Sajjad Fouladvand
    Department of Computer Science, Institute for Biomedical Informatics, University of Kentucky, Lexington, KY, USA.
  • Emma Pierson
    Department of Computer Science, Stanford University, Stanford, CA, USA.
  • Ivana Jankovic
    Division of Endocrinology, Department of Medicine, Stanford University, School of Medicine, Stanford, California, USA.
  • David Ouyang
    Division of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Jonathan H Chen
    Stanford Center for Biomedical Informatics Research, Stanford, CA.
  • Roxana Daneshjou
    1Department of Biomedical Data Science, Stanford School of Medicine, Stanford, California, USA; email: roxanad@stanford.edu.

Keywords

External Resources

Popular Topics
Recent Journals