<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>8(11)</volume><submitter>Yun D</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>To investigate the attitude and formal suggestions on talent cultivation in the field of medical artificial intelligence (AI).&lt;h4>Methods&lt;/h4>An electronic questionnaire was sent to both medical-related field or non-medical field population using the WenJuanXing web-application via social media. The questionnaire was designed to collect: (I) demographic information; (II) perception of medical AI; (III) willingness to participate in the medical AI related teaching activities; (IV) teaching content of medical AI; (V) the role of medical AI teaching; (VI) future career planning. Respondents' anonymity was ensured.&lt;h4>Results&lt;/h4>A total of 710 respondents provided valid answers to the questionnaire (57.75% medical related, 42.25% non-medical). About 73.8% of respondents acq</pubmed_abstract><journal>Annals of translational medicine</journal><pagination>708</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7327345</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Attitudes towards medical artificial intelligence talent cultivation: an online survey study.</pubmed_title><pmcid>PMC7327345</pmcid><pubmed_authors>Liu Y</pubmed_authors><pubmed_authors>Zou Y</pubmed_authors><pubmed_authors>Liu Z</pubmed_authors><pubmed_authors>Zhao L</pubmed_authors><pubmed_authors>Lin D</pubmed_authors><pubmed_authors>Xiang Y</pubmed_authors><pubmed_authors>Lin H</pubmed_authors><pubmed_authors>Yun D</pubmed_authors><pubmed_authors>Guo C</pubmed_authors><pubmed_authors>Xie P</pubmed_authors><pubmed_authors>Wu X</pubmed_authors></additional><is_claimable>false</is_claimable><name>Attitudes towards medical artificial intelligence talent cultivation: an online survey study.</name><description>&lt;h4>Background&lt;/h4>To investigate the attitude and formal suggestions on talent cultivation in the field of medical artificial intelligence (AI).&lt;h4>Methods&lt;/h4>An electronic questionnaire was sent to both medical-related field or non-medical field population using the WenJuanXing web-application via social media. The questionnaire was designed to collect: (I) demographic information; (II) perception of medical AI; (III) willingness to participate in the medical AI related teaching activities; (IV) teaching content of medical AI; (V) the role of medical AI teaching; (VI) future career planning. Respondents' anonymity was ensured.&lt;h4>Results&lt;/h4>A total of 710 respondents provided valid answers to the questionnaire (57.75% medical related, 42.25% non-medical). About 73.8% of respondents acq</description><dates><release>2020-01-01T00:00:00Z</release><publication>2020 Jun</publication><modification>2025-04-20T03:13:31.21Z</modification><creation>2025-04-20T03:13:31.21Z</creation></dates><accession>S-EPMC7327345</accession><cross_references><pubmed>32617328</pubmed><doi>10.21037/atm.2019.12.149</doi></cross_references></HashMap>