Translating Data Science Results into Precision Oncology Decisions: A Mini Review

Enrico Capobianco; Marco Dominietto

doi:10.3390/jcm12020438

Translating Data Science Results into Precision Oncology Decisions: A Mini Review

J Clin Med. 2023 Jan 5;12(2):438. doi: 10.3390/jcm12020438.

Authors

Enrico Capobianco¹, Marco Dominietto²

Affiliations

¹ The Jackson Laboratory, 10 Discovery Drive, Farmington, CT 06032, USA.
² Paul Scherrer Institut, Forschungsstrasse 111, 5232 Villigen, Switzerland.

Abstract

While reviewing and discussing the potential of data science in oncology, we emphasize medical imaging and radiomics as the leading contextual frameworks to measure the impacts of Artificial Intelligence (AI) and Machine Learning (ML) developments. We envision some domains and research directions in which radiomics should become more significant in view of current barriers and limitations.

Keywords: data science; decision systems; radiomics.

Publication types

Review

Grants and funding

EC acknowledges support from JAX Computational Sciences, JAX Cancer Center (JAXCC) and NCI CCSG (P30CA034196) and support from grant NSF 19-500, DMS 1918925/1922843.