Potential of AI and ML in oncology research including diagnosis, treatment and future directions: A comprehensive prospective
Akanksha Gupta
1
,
Samyak Bajaj
1
,
Priyanshu Nema
1
,
Arpana Purohit
1
,
Varsha Kashaw
2
,
Vandana Soni
1
,
Sushil K. Kashaw
1
2
Sagar Institute of Pharmaceutical Sciences, Sagar, M.P., India
|
Publication type: Journal Article
Publication date: 2025-05-01
scimago Q1
wos Q1
SJR: 1.447
CiteScore: 13.0
Impact factor: 6.3
ISSN: 00104825, 18790534
Abstract
Artificial intelligence (AI) and machine learning (ML) have emerged as transformative tools in cancer research, offering the ability to process huge data rapidly and make precise therapeutic decisions. Over the last decade, AI, particularly deep learning (DL) and machine learning (ML), has significantly enhanced cancer prediction, diagnosis, and treatment by leveraging algorithms such as convolutional neural networks (CNNs) and multi-layer perceptrons (MLPs). These technologies provide reliable, efficient solutions for managing aggressive diseases like cancer, which have high recurrence and mortality rates. This review prospective highlights the applications of AI in oncology, a long with FDA-approved technologies like EFAI RTSuite CT HN-Segmentation System, Quantib Prostate, and Paige Prostate, and explore their role in advancing cancer detection, personalized care, and treatment. Furthermore, we also explored broader applications of AI in healthcare, addressing challenges, limitations, regulatory considerations, and ethical implications. By presenting these advancements, we underscore AI's potential to revolutionize cancer care, management and treatment.
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Gupta A. et al. Potential of AI and ML in oncology research including diagnosis, treatment and future directions: A comprehensive prospective // Computers in Biology and Medicine. 2025. Vol. 189. p. 109918.
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Gupta A., Bajaj S., Nema P., Purohit A., Kashaw V., Soni V., Kashaw S. K. Potential of AI and ML in oncology research including diagnosis, treatment and future directions: A comprehensive prospective // Computers in Biology and Medicine. 2025. Vol. 189. p. 109918.
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TY - JOUR
DO - 10.1016/j.compbiomed.2025.109918
UR - https://linkinghub.elsevier.com/retrieve/pii/S0010482525002690
TI - Potential of AI and ML in oncology research including diagnosis, treatment and future directions: A comprehensive prospective
T2 - Computers in Biology and Medicine
AU - Gupta, Akanksha
AU - Bajaj, Samyak
AU - Nema, Priyanshu
AU - Purohit, Arpana
AU - Kashaw, Varsha
AU - Soni, Vandana
AU - Kashaw, Sushil K.
PY - 2025
DA - 2025/05/01
PB - Elsevier
SP - 109918
VL - 189
SN - 0010-4825
SN - 1879-0534
ER -
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@article{2025_Gupta,
author = {Akanksha Gupta and Samyak Bajaj and Priyanshu Nema and Arpana Purohit and Varsha Kashaw and Vandana Soni and Sushil K. Kashaw},
title = {Potential of AI and ML in oncology research including diagnosis, treatment and future directions: A comprehensive prospective},
journal = {Computers in Biology and Medicine},
year = {2025},
volume = {189},
publisher = {Elsevier},
month = {may},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0010482525002690},
pages = {109918},
doi = {10.1016/j.compbiomed.2025.109918}
}