Place of Artificial Intelligence in Oncology: Literature review and Perspectives

Artificial Intelligence and Healthcare Artificial Intelligence (AI) is a subfield of computer science concerned with algorithms that perform tasks typically associated with human cognition. AI has been applied to medical problems for many years, but accelerated adoption in healthcare is now motivated by a growth in data volume and comprehensiveness, improvements in computational power, and an increase in innovative software developers. Modern AI technology can provide significant insight and benefit by processing a diverse set of data types related to a problem domain. Beyond the capability to recognize patterns in data, AI algorithms can synthesize large volumes of information from multiple sources quickly. In healthcare, common applications include identifying conditions, risk factors, or patterns to support clinical decision-making, population health, and discovery. Cancer is a broad class of devastating diseases that grows exponentially in complexity as it progresses, creating a difficult analytical space for reasoning and management. Ongoing work suggests that AI may be particularly well suited to meeting this challenge, but widespread impact in the clinical domain remains elusive.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-20
DOI
https://doi.org/10.5281/zenodo.17284877
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
0.00
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article

Place of Artificial Intelligence in Oncology: Literature review and Perspectives

Zenodo (CERN European Organization for Nuclear Research)
Genetic and phenotypic traits in livestock
article

Place of Artificial Intelligence in Oncology: Literature review and Perspectives

article en

Abstract

Artificial Intelligence and Healthcare Artificial Intelligence (AI) is a subfield of computer science concerned with algorithms that perform tasks typically associated with human cognition. AI has been applied to medical problems for many years, but accelerated adoption in healthcare is now motivated by a growth in data volume and comprehensiveness, improvements in computational power, and an increase in innovative software developers. Modern AI technology can provide significant insight and benefit by processing a diverse set of data types related to a problem domain. Beyond the capability to recognize patterns in data, AI algorithms can synthesize large volumes of information from multiple sources quickly. In healthcare, common applications include identifying conditions, risk factors, or patterns to support clinical decision-making, population health, and discovery. Cancer is a broad class of devastating diseases that grows exponentially in complexity as it progresses, creating a difficult analytical space for reasoning and management. Ongoing work suggests that AI may be particularly well suited to meeting this challenge, but widespread impact in the clinical domain remains elusive.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 35%
Genetic and phenotypic traits in livestock
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Place of Artificial Intelligence in Oncology: Literature review and Perspectives · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS