This paper is in the following e-collection/theme issue:

Viewpoints and Perspectives (619) Viewpoints on and Experiences with Digital Technologies in Health (99) Crowdsourcing and Mechanical Turks (103) Artificial Intelligence (2129) Machine Learning (2076) Clinical Information and Decision Making (1915) Advanced Data Analytics in eHealth (209) Precision Medicine (159)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51138, first published .
A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health

A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health

A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health

Authors of this article:

Peter Washington1 Author Orcid Image
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Journals

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  2. Lin K, Rasool A, Surabhi S, Mutlu C, Zhang H, Wall D, Washington P. Aiding Large Language Models Using Clinical Scoresheets for Neurobehavioral Diagnostic Classification From Text: Algorithm Development and Validation. JMIR AI 2025;4:e75030 View
  3. Branda F, Ciccozzi M, Scarpa F. Artificial intelligence in scientific research: Challenges, opportunities and the imperative of a human-centric synergy. Journal of Informetrics 2025;19(4):101727 View
  4. Racacho K, Shiau Y, Villa R, Mahri S, Tang M, Lin T, Li Y. The tumor immune microenvironment: implications for cancer immunotherapy, treatment strategies, and monitoring approaches. Frontiers in Immunology 2025;16 View
  5. Azizian P, Honarmand M, Jaiswal A, Kline A, Dunlap K, Washington P, Wall D. Multimodal LLM vs. Human-Measured Features for AI Predictions of Autism in Home Videos. Algorithms 2025;18(11):687 View