Future of Artificial Intelligence Applications in Cancer Care: A Global Cross-Sectional Survey of Researchers.
Cancer significantly contributes to global mortality, with 9.3 million annual deaths. To alleviate this burden, the utilization of artificial intelligence (AI) applications has been proposed in various domains of oncology. However, the potential applications of AI and the barriers to its widespread...
| Publicado en: | Current Oncology Vol. 30; no. 3; pp. 3432 - 3447 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
MDPI
Mar2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=162747227&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 162747227 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 11980052 5EKK jtl: Current Oncology issn: 11980052 maglogo: N pubinfo: dt: Mar2023 vid: 30 iid: 3 pid: 97109 pub: MDPI artinfo: ui: 162747227 10.3390/curroncol30030260 162747227 ppf: 3432 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Future of Artificial Intelligence Applications in Cancer Care: A Global Cross-Sectional Survey of Researchers. aug: au: Cabral, Bernardo Pereira Braga, Luiza Amara Maciel Syed-Abdul, Shabbir Mota, Fabio Batista affil: Department of Economics, Federal University of Bahia, Salvador 40060-300, Brazil sug: ab: Cancer significantly contributes to global mortality, with 9.3 million annual deaths. To alleviate this burden, the utilization of artificial intelligence (AI) applications has been proposed in various domains of oncology. However, the potential applications of AI and the barriers to its widespread adoption remain unclear. This study aimed to address this gap by conducting a cross-sectional, global, web-based survey of over 1000 AI and cancer researchers. The results indicated that most respondents believed AI would positively impact cancer grading and classification, follow-up services, and diagnostic accuracy. Despite these benefits, several limitations were identified, including difficulties incorporating AI into clinical practice and the lack of standardization in cancer health data. These limitations pose significant challenges, particularly regarding testing, validation, certification, and auditing AI algorithms and systems. The results of this study provide valuable insights for informed decision-making for stakeholders involved in AI and cancer research and development, including individual researchers and research funding agencies. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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