Accepted for/Published in: JMIR Medical Education

Date Submitted:

Open Peer Review Period: -

Date Accepted:

Date Submitted to PubMed:

closed for review but you can still tweet
  • Rongxi P, Weiru W, Xiaoli Z, Zhong Y, Youcai D
  • Evaluating Large Language Models' Capabilities in Laboratory Hematology: A Case Study Based on the Chinese Medical Laboratory Technician Examination
  • JMIR Medical Education
  • DOI: 10.2196/11848
  • PMID: 30303485
  • PMCID: 6352016
Preprints Accepted Manuscript

Abstract accepted

Background:

Social media can be a useful strategy for recruiting hard-to-reach, stigmatized populations into research studies; however, it may also introduce risks for participant and research team exposure to negative comments. Currently, there is no published formal social media recruitment and monitoring guidelines that specifically address harm reduction for social media recruitment of marginalized populations.

Objective:

Social media can be a useful strategy for recruiting hard-to-reach, stigmatized populations into research studies; however, it may also introduce risks for participant and research team exposure to negative comments. Currently, there is no published formal social media recruitment and monitoring guidelines that specifically address harm reduction for social media recruitment of marginalized populations.

Methods:

Social media can be a useful strategy for recruiting hard-to-reach, stigmatized populations into research studies; however, it may also introduce risks for participant and research team exposure to negative comments. Currently, there is no published formal social media recruitment and monitoring guidelines that specifically address harm reduction for social media recruitment of marginalized populations.

As per the author’s request the PDF is not available.
Copyright

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it’s website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.

Citation

Please cite as:

Rongxi P, Weiru W, Xiaoli Z, Zhong Y, Youcai D

Evaluating Large Language Models' Capabilities in Laboratory Hematology: A Case Study Based on the Chinese Medical Laboratory Technician Examination

JMIR Medical Education

DOI: 10.2196/14886

URL: https://preprints.jmir.org/preprint/11848

PMID: 31789598

PMCID: 6352016

Evaluating Large Language Models' Capabilities in Laboratory Hematology: A Case Study Based on the Chinese Medical Laboratory Technician Examination

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