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Artificial intelligence in oncology: chances and pitfalls
Artificial intelligence (AI) has been available in rudimentary forms for many decades. Early AI programs were successful in niche areas such as chess or handwriting recognition. However, AI methods had little practical impact on the practice of medicine until recently. Beginning around 2012, AI has...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374782/ https://www.ncbi.nlm.nih.gov/pubmed/36920564 http://dx.doi.org/10.1007/s00432-023-04666-6 |
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author | Kather, Jakob Nikolas |
author_facet | Kather, Jakob Nikolas |
author_sort | Kather, Jakob Nikolas |
collection | PubMed |
description | Artificial intelligence (AI) has been available in rudimentary forms for many decades. Early AI programs were successful in niche areas such as chess or handwriting recognition. However, AI methods had little practical impact on the practice of medicine until recently. Beginning around 2012, AI has emerged as an increasingly important tool in healthcare, and AI-based devices are now approved for clinical use. These devices are capable of processing image data, making diagnoses, and predicting biomarkers for solid tumors, among other applications. Despite this progress, the development of AI in medicine is still in its early stages, and there have been exponential technical advancements since 2022, with some AI programs now demonstrating human-level understanding of image and text data. In the past, technical advances have led to new medical applications with a delay of a few years. Therefore, now we might be at the beginning of a new era in which AI will become even more important in clinical practice. It is essential that this transformation is humane and evidence based, and physicians must take a leading role in ensuring this, particularly in hematology and oncology. |
format | Online Article Text |
id | pubmed-10374782 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-103747822023-07-29 Artificial intelligence in oncology: chances and pitfalls Kather, Jakob Nikolas J Cancer Res Clin Oncol Review Artificial intelligence (AI) has been available in rudimentary forms for many decades. Early AI programs were successful in niche areas such as chess or handwriting recognition. However, AI methods had little practical impact on the practice of medicine until recently. Beginning around 2012, AI has emerged as an increasingly important tool in healthcare, and AI-based devices are now approved for clinical use. These devices are capable of processing image data, making diagnoses, and predicting biomarkers for solid tumors, among other applications. Despite this progress, the development of AI in medicine is still in its early stages, and there have been exponential technical advancements since 2022, with some AI programs now demonstrating human-level understanding of image and text data. In the past, technical advances have led to new medical applications with a delay of a few years. Therefore, now we might be at the beginning of a new era in which AI will become even more important in clinical practice. It is essential that this transformation is humane and evidence based, and physicians must take a leading role in ensuring this, particularly in hematology and oncology. Springer Berlin Heidelberg 2023-03-15 2023 /pmc/articles/PMC10374782/ /pubmed/36920564 http://dx.doi.org/10.1007/s00432-023-04666-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Kather, Jakob Nikolas Artificial intelligence in oncology: chances and pitfalls |
title | Artificial intelligence in oncology: chances and pitfalls |
title_full | Artificial intelligence in oncology: chances and pitfalls |
title_fullStr | Artificial intelligence in oncology: chances and pitfalls |
title_full_unstemmed | Artificial intelligence in oncology: chances and pitfalls |
title_short | Artificial intelligence in oncology: chances and pitfalls |
title_sort | artificial intelligence in oncology: chances and pitfalls |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374782/ https://www.ncbi.nlm.nih.gov/pubmed/36920564 http://dx.doi.org/10.1007/s00432-023-04666-6 |
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