Citation

Shorna, Sifat Jahan and Majumder, Sreya and Rahman, Diya and Jahan, Fariha and Noori, Sheak Rashed Haider and Hui, Liew Tze and Nandi, Dip and Rahman, Mashiour (2026) Predictive modeling for survival-related outcomes in lung cancer patients with brain metastases: a mini-review. Frontiers in Oncology, 16. ISSN 2234-943X

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Abstract

Predicting survival in lung cancer patients, particularly those with brain metastases, is crucial for personalizing treatment plans and estimating patient prognosis. This minireview synthesizes findings from fifteen recent studies published between 2020 and 2026, focusing on survival prediction in lung cancer patients with brain metastases, with key outcomes including overall survival, progression-free survival, and intracranial progressionfree survival. Traditional and current approaches for predicting survival are discussed, along with comparisons between unimodal and multimodal approaches. Moreover, the strengths and limitations of existing methods are critically analyzed. The findings emphasize the potential of advanced predictive modeling to inform personalized treatment plans and improve survival outcomes in this high-risk population.

Item Type:	Article
Uncontrolled Keywords:	brain metastases, deep learning, lung cancer, machine learning, multimodal learning, survival prediction
Subjects:	R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	04 Sep 2026 04:23
Last Modified:	04 Sep 2026 04:23
URII:	http://shdl.mmu.edu.my/id/eprint/16712

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