Artificial intelligence and its potential in oncology
Abstract
The two main branches associated with Artificial Intelligence (AI) in medicine are virtual and physical. The virtual component includes machine learning (ML) and algorithms, whereas physical AI includes medical devices and robots for delivering care. AI is used successfully in tumour segmentation, histopathological diagnosis, tracking tumour development, and prognosis prediction. CURATE.AI, developed at the National University of Singapore, is a platform that automatically decides the optimum dose of drugs for a durable response, allowing the patient to resume a completely normal life. With the involvement of technology multinationals, such as Google and Microsoft, in AI and healthcare in association with leading healthcare companies, the future of AI in healthcare looks very promising.
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AI can improve medical practice, address staff shortages, and enhance diagnostic efficiency.
“Artificial intelligence (AI) is transforming multiple industries, including healthcare and medical education, by enhancing diagnostic accuracy, supporting clinical decision-making, and addressing workforce shortages [1, 2].”
From Knowledge, attitudes, and practices toward AI technology (ChatGPT) among nursing students at Palestinian universities (2025) · cites this paper as [2]
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References 37 · Cited by 53
- Authors
- Londhe, V. Y., & Bhasin, B.
- Affiliations
- Narsee Monjee Institute of Management Studies (IN)
- Corresponding author
- Londhe, Vaishali Y.
- ORCID
- Londhe, Vaishali Y.
- Venue
- Drug Discovery Today
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 24
- Issue
- 1
- Pages
- 228-232
- ISSN
- 1359-6446 (ISSN-L)
- OpenAlex
- W2896741512
- Cited by
- 53
- References
- 37
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 3 · 2023: 13 · 2022: 7 · 2021: 5 · 2020: 14 · 2019: 1
- FWCI
- 0.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Drug Discovery Today (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Keywords
- artificial intelligence in oncology, machine learning, tumor segmentation, histopathological diagnosis, tumor tracking, outcome prediction, drug dose optimization, medical robotics, medical devices, artificial intelligence in healthcare
- MeSH terms
- Artificial Intelligence, Humans, Medical Oncology
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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