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FUTURE OF ARTIFICIAL INTELLIGENCE APPLICATIONS IN CANCER CARE: A GLOBAL CROSS-SECTIONAL SURVEY OF RESEARCHERS
Affilliation
Universidade Federal da Bahia. Departamento de Economia. Salvador, BA, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Comunicação Celular. Rio de Janeiro, RJ, Brasil.
Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan / School of Gerontology and Long-Term Care, College of Nursing, Taipei Medical University, Taipei 110, Taiwan.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Comunicação Celular. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Comunicação Celular. Rio de Janeiro, RJ, Brasil.
Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 110, Taiwan / School of Gerontology and Long-Term Care, College of Nursing, Taipei Medical University, Taipei 110, Taiwan.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Comunicação Celular. Rio de Janeiro, RJ, Brasil.
Abstract
Abstract: 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 crosssectional,
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.
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