How to critically appraise and direct the trajectory of AI development and application in oncology
As artificial intelligence (AI) advances, oncologists stand at the forefront of a transformative era in healthcare. AI, which empowers machines to learn from data, make decisions, and carry out tasks typically requiring human intelligence, is revolutionizing our clinical landscape. It promises strea...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-09-01
|
| Series: | ESMO Real World Data and Digital Oncology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949820124000444 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850140987874082816 |
|---|---|
| author | R.S.N. Fehrmann M. van Kruchten E.G.E. de Vries |
| author_facet | R.S.N. Fehrmann M. van Kruchten E.G.E. de Vries |
| author_sort | R.S.N. Fehrmann |
| collection | DOAJ |
| description | As artificial intelligence (AI) advances, oncologists stand at the forefront of a transformative era in healthcare. AI, which empowers machines to learn from data, make decisions, and carry out tasks typically requiring human intelligence, is revolutionizing our clinical landscape. It promises streamlined workflows, enhanced diagnostic accuracy, and personalized treatments tailored to each patient’s unique profile. In the vast sea of patient data, AI serves as a guiding compass, ensuring no detail is overlooked, amplifying clinical acumen, and refining treatment decisions. However, to ensure AI’s benefits reach patients effectively, it is imperative that oncologists actively guide its development and application. This overview aims to equip oncologists with the tools to critically appraise and influence the trajectory of AI in oncology, ensuring its integration leads to meaningful advances in patient care. |
| format | Article |
| id | doaj-art-2a6c190762f34cdd8b183bdead3af446 |
| institution | OA Journals |
| issn | 2949-8201 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | ESMO Real World Data and Digital Oncology |
| spelling | doaj-art-2a6c190762f34cdd8b183bdead3af4462025-08-20T02:29:37ZengElsevierESMO Real World Data and Digital Oncology2949-82012024-09-01510006610.1016/j.esmorw.2024.100066How to critically appraise and direct the trajectory of AI development and application in oncologyR.S.N. Fehrmann0M. van Kruchten1E.G.E. de Vries2Correspondence to: Prof. Rudolf S. N. Fehrmann, Department of Medical Oncology, University Medical Center Groningen, P.O. Box 30.001, 9700 RB Groningen, the Netherlands. Tel: +31-503612821; Fax: +31-503614862; Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the NetherlandsDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the NetherlandsDepartment of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, the NetherlandsAs artificial intelligence (AI) advances, oncologists stand at the forefront of a transformative era in healthcare. AI, which empowers machines to learn from data, make decisions, and carry out tasks typically requiring human intelligence, is revolutionizing our clinical landscape. It promises streamlined workflows, enhanced diagnostic accuracy, and personalized treatments tailored to each patient’s unique profile. In the vast sea of patient data, AI serves as a guiding compass, ensuring no detail is overlooked, amplifying clinical acumen, and refining treatment decisions. However, to ensure AI’s benefits reach patients effectively, it is imperative that oncologists actively guide its development and application. This overview aims to equip oncologists with the tools to critically appraise and influence the trajectory of AI in oncology, ensuring its integration leads to meaningful advances in patient care.http://www.sciencedirect.com/science/article/pii/S2949820124000444artificial intelligenceAI regulatory frameworks |
| spellingShingle | R.S.N. Fehrmann M. van Kruchten E.G.E. de Vries How to critically appraise and direct the trajectory of AI development and application in oncology ESMO Real World Data and Digital Oncology artificial intelligence AI regulatory frameworks |
| title | How to critically appraise and direct the trajectory of AI development and application in oncology |
| title_full | How to critically appraise and direct the trajectory of AI development and application in oncology |
| title_fullStr | How to critically appraise and direct the trajectory of AI development and application in oncology |
| title_full_unstemmed | How to critically appraise and direct the trajectory of AI development and application in oncology |
| title_short | How to critically appraise and direct the trajectory of AI development and application in oncology |
| title_sort | how to critically appraise and direct the trajectory of ai development and application in oncology |
| topic | artificial intelligence AI regulatory frameworks |
| url | http://www.sciencedirect.com/science/article/pii/S2949820124000444 |
| work_keys_str_mv | AT rsnfehrmann howtocriticallyappraiseanddirectthetrajectoryofaidevelopmentandapplicationinoncology AT mvankruchten howtocriticallyappraiseanddirectthetrajectoryofaidevelopmentandapplicationinoncology AT egedevries howtocriticallyappraiseanddirectthetrajectoryofaidevelopmentandapplicationinoncology |