Description

• Title:
  The role of artificial intelligence in cancer diagnostics - a review
• Creator:
  Stanicki, Paweł;
  Nowakowska, Katarzyna;
  Piwoński, Michał;
  Żak, Klaudia;
  Niedobylski, Sylwiusz;
  Zaremba, Bartłomiej;
  Oszczędłowski, Paweł
• Description:
  Introduction and purposeArtificial intelligence (AI) is more advanced than ever and finds more and more new applications. Attempts are being made to use computer data analysis in medicine. The aim of this study is to summarize the knowledge on the use of AI in the diagnosis of breast, prostate, skin and colorectal cancer with particular emphasis on the applications and effectiveness of AI in making diagnoses. A brief description of the state of knowledgeThe most frequently used form of artificial intelligence in diagnostics are algorithms that analyze databases and recognize patterns. They can capture the features of samples characteristic of tumors, such as abnormal cells in the biopsy material or the alarming size and color of the skin lesion. Additionally, AI is capable of analyzing magnetic resonance images, radiographs, and other standardized test results. In most cases, AI is more effective than clinicians, sometimes as effective as they are, and almost never less effective. As a rule, the most accurate and adequate diagnosis can be obtained by joining the forces of AI and medical specialists. Working with learning algorithms requires the use of very extensive data sets. Every effort should be made to protect sensitive information from patients' medical history. ConclusionsThe results of research on the effectiveness of AI in cancer diagnostics are very promising. Further research and development of information technology systems may positively affect the quality and effectiveness of tumor diagnostics.
• Object availability:
  free access
• Rights: http://creativecommons.org/licenses/by-nc-sa/4.0 ;
  Prawa autorskie (c) 2021 © The Author(s)
• Date:
  2021.09.07
• Type:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion
• Language:
  English
• Source:
  Journal of Education, Health and Sport; Vol. 11 No. 9 (2021); 113-122;
  Journal of Education, Health and Sport; Tom 11 Nr 9 (2021); 113-122;
  2391-8306
• Format:
  application/pdf
• Publisher:
  Nicolaus Copernicus University, Toruń, Poland
• Relation: https://apcz.umk.pl/JEHS/article/view/JEHS.2021.11.09.016/29630
• Subject:
  artificial intelligence;
  breast cancer;
  prostate cancer;
  skin cancer;
  melanoma;
  colorectal cancer
• Identifier: https://apcz.umk.pl/JEHS/article/view/JEHS.2021.11.09.016
• Data provider:
  Akademicka Platforma Czasopism
• Can I use it?:
  seek permission
• Type:
  text