A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health
Modern machine learning approaches have led to performant diagnostic models for a variety of health conditions. Several machine learning approaches, such as decision trees and deep neural networks, can, in principle, approximate any function. However, this power can be considered to be bo...
Main Author: | Peter Washington |
---|---|
Format: | Article |
Language: | English |
Published: |
JMIR Publications
2024-04-01
|
Series: | Journal of Medical Internet Research |
Online Access: | https://www.jmir.org/2024/1/e51138 |
Similar Items
-
Validation and tuning of in situ transcriptomics image processing workflows with crowdsourced annotations.
by: Jenny M Vo-Phamhi, et al.
Published: (2021-08-01) -
Digitally Diagnosing Multiple Developmental Delays Using Crowdsourcing Fused With Machine Learning: Protocol
for a Human-in-the-Loop Machine Learning Study
by: Aditi Jaiswal, et al.
Published: (2024-02-01) -
Humans in the loop: incorporating expert and crowdsourced knowledge for predictions using survey data
by: Filippova, A, et al.
Published: (2019) -
The question of the efficiency of the workflow of loop propellers
by: A. V. Mesropyan, et al.
Published: (2023-06-01) -
Crowdsourcing Precision Cerebrovascular Health: Imaging and Cloud Seeding A Million Brains Initiative™
by: David S Liebeskind
Published: (2016-11-01)