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- Title
Recent Advances in the Field of Artificial Intelligence for Precision Medicine in Patients with a Diagnosis of Metastatic Cutaneous Melanoma.
- Authors
Higgins, Hayley; Nakhla, Abanoub; Lotfalla, Andrew; Khalil, David; Doshi, Parth; Thakkar, Vandan; Shirini, Dorsa; Bebawy, Maria; Ammari, Samy; Lopci, Egesta; Schwartz, Lawrence H.; Postow, Michael; Dercle, Laurent
- Abstract
Standard-of-care medical imaging techniques such as CT, MRI, and PET play a critical role in managing patients diagnosed with metastatic cutaneous melanoma. Advancements in artificial intelligence (AI) techniques, such as radiomics, machine learning, and deep learning, could revolutionize the use of medical imaging by enhancing individualized image-guided precision medicine approaches. In the present article, we will decipher how AI/radiomics could mine information from medical images, such as tumor volume, heterogeneity, and shape, to provide insights into cancer biology that can be leveraged by clinicians to improve patient care both in the clinic and in clinical trials. More specifically, we will detail the potential role of AI in enhancing detection/diagnosis, staging, treatment planning, treatment delivery, response assessment, treatment toxicity assessment, and monitoring of patients diagnosed with metastatic cutaneous melanoma. Finally, we will explore how these proof-of-concept results can be translated from bench to bedside by describing how the implementation of AI techniques can be standardized for routine adoption in clinical settings worldwide to predict outcomes with great accuracy, reproducibility, and generalizability in patients diagnosed with metastatic cutaneous melanoma.
- Subjects
ARTIFICIAL intelligence; INDIVIDUALIZED medicine; MELANOMA; COMPUTER-assisted image analysis (Medicine); DIAGNOSIS; DIAGNOSTIC imaging
- Publication
Diagnostics (2075-4418), 2023, Vol 13, Issue 22, p3483
- ISSN
2075-4418
- Publication type
Article
- DOI
10.3390/diagnostics13223483