Just how transformative will AI/ML be for immuno-oncology?
J Immunother Cancer
; 12(3)2024 Mar 25.
Article
en En
| MEDLINE
| ID: mdl-38531545
ABSTRACT
Immuno-oncology involves the study of approaches which harness the patient's immune system to fight malignancies. Immuno-oncology, as with every other biomedical and clinical research field as well as clinical operations, is in the midst of technological revolutions, which vastly increase the amount of available data. Recent advances in artificial intelligence and machine learning (AI/ML) have received much attention in terms of their potential to harness available data to improve insights and outcomes in many areas including immuno-oncology. In this review, we discuss important aspects to consider when evaluating the potential impact of AI/ML applications in the clinic. We highlight four clinical/biomedical challenges relevant to immuno-oncology and how they may be able to be addressed by the latest advancements in AI/ML. These challenges include (1) efficiency in clinical workflows, (2) curation of high-quality image data, (3) finding, extracting and synthesizing text knowledge as well as addressing, and (4) small cohort size in immunotherapeutic evaluation cohorts. Finally, we outline how advancements in reinforcement and federated learning, as well as the development of best practices for ethical and unbiased data generation, are likely to drive future innovations.
Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Inteligencia Artificial
/
Neoplasias
Límite:
Humans
Idioma:
En
Revista:
J Immunother Cancer
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos