Large Language Models in Oncology: Revolution or Cause for Concern?

Author:

Caglayan Aydin1,Slusarczyk Wojciech2ORCID,Rabbani Rukhshana Dina1ORCID,Ghose Aruni13456ORCID,Papadopoulos Vasileios7,Boussios Stergios128910ORCID

Affiliation:

1. Department of Medical Oncology, Medway NHS Foundation Trust, Gillingham ME7 5NY, UK

2. Kent Medway Medical School, University of Kent, Canterbury CT2 7LX, UK

3. Department of Medical Oncology, Barts Cancer Centre, St Bartholomew’s Hospital, Barts Heath NHS Trust, London EC1A 7BE, UK

4. Department of Medical Oncology, Mount Vernon Cancer Centre, East and North Hertfordshire Trust, London HA6 2RN, UK

5. Health Systems and Treatment Optimisation Network, European Cancer Organisation, 1040 Brussels, Belgium

6. Oncology Council, Royal Society of Medicine, London W1G 0AE, UK

7. Kent and Canterbury Hospital, Canterbury CT1 3NG, UK

8. Faculty of Life Sciences & Medicine, School of Cancer & Pharmaceutical Sciences, King’s College London, Strand Campus, London WC2R 2LS, UK

9. Faculty of Medicine, Health, and Social Care, Canterbury Christ Church University, Canterbury CT2 7PB, UK

10. AELIA Organization, 9th Km Thessaloniki—Thermi, 57001 Thessaloniki, Greece

Abstract

The technological capability of artificial intelligence (AI) continues to advance with great strength. Recently, the release of large language models has taken the world by storm with concurrent excitement and concern. As a consequence of their impressive ability and versatility, their provide a potential opportunity for implementation in oncology. Areas of possible application include supporting clinical decision making, education, and contributing to cancer research. Despite the promises that these novel systems can offer, several limitations and barriers challenge their implementation. It is imperative that concerns, such as accountability, data inaccuracy, and data protection, are addressed prior to their integration in oncology. As the progression of artificial intelligence systems continues, new ethical and practical dilemmas will also be approached; thus, the evaluation of these limitations and concerns will be dynamic in nature. This review offers a comprehensive overview of the potential application of large language models in oncology, as well as concerns surrounding their implementation in cancer care.

Publisher

MDPI AG

Reference93 articles.

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