Combining machine learning models and rule engines in clinical decision systems: Exploring optimal aggregation methods for vaccine hesitancy prediction.

Journal: Computers in biology and medicine
PMID: 39983355

Abstract

BACKGROUND: With the increasing application of artificial intelligence (AI) technologies in the healthcare sector and the emergence of new solutions, such as large language models, there is a growing need to combine medical knowledge, often expressed as clinical rules, with advances in machine learning (ML) offering higher prediction accuracy at the expense of decision-making transparency.

Authors

  • Slawomir Kierner
    Lodz University of Technology, Faculty of Electrical, Electronic, Computer and Control Engineering, 27 Isabella Street, 02116 Boston, MA, USA. Electronic address: kierner.s@gmail.com.
  • Piotr Kierner
    Department of Genetics - Blavatnik Institute, Sinclair Lab, Harvard Medical School, D 77 Avenue Louis Pasteur, Boston, MA 02115, USA.
  • Jacek Kucharski
    Institute of Applied Computer Science, Lodz University of Technology, Stefanowskiego 18/22, 90-537 Łódź, Poland.

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