Precision medicine approach to melanoma immunotherapy: Predicting response, adverse events, and hospital admissions using machine learning and explainable artificial intelligence

Lakshya Sharma; Vaishnavi Balaji; Alvin Katumba; Esha Mohan; Sola Michael. Adeleke

doi:10.1158/1557-3265.AIMACHINE-A015

Precision medicine approach to melanoma immunotherapy: Predicting response, adverse events, and hospital admissions using machine learning and explainable artificial intelligence

Lakshya Sharma, Vaishnavi Balaji, Alvin Katumba, Esha Mohan, Sola Michael. Adeleke

School of Medicine

Research output: Contribution to journal › Abstract › peer-review

Original language	English
Pages (from-to)	A015-A015
Number of pages	1
Journal	Clinical Cancer Research
Volume	31
Issue number	13
DOIs	https://doi.org/10.1158/1557-3265.AIMACHINE-A015
Publication status	Published - 10 Jul 2025

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10.1158/1557-3265.AIMACHINE-A015

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title = "Precision medicine approach to melanoma immunotherapy: Predicting response, adverse events, and hospital admissions using machine learning and explainable artificial intelligence",

author = "Lakshya Sharma and Vaishnavi Balaji and Alvin Katumba and Esha Mohan and Adeleke, \{Sola Michael.\}",

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Precision medicine approach to melanoma immunotherapy: Predicting response, adverse events, and hospital admissions using machine learning and explainable artificial intelligence. / Sharma, Lakshya; Balaji, Vaishnavi; Katumba, Alvin et al.
In: Clinical Cancer Research, Vol. 31, No. 13, 10.07.2025, p. A015-A015.

Research output: Contribution to journal › Abstract › peer-review

TY - JOUR

T1 - Precision medicine approach to melanoma immunotherapy

T2 - Predicting response, adverse events, and hospital admissions using machine learning and explainable artificial intelligence

AU - Sharma, Lakshya

AU - Balaji, Vaishnavi

AU - Katumba, Alvin

AU - Mohan, Esha

AU - Adeleke, Sola Michael.

PY - 2025/7/10

Y1 - 2025/7/10

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DO - 10.1158/1557-3265.AIMACHINE-A015

M3 - Abstract

SN - 1078-0432

VL - 31

SP - A015-A015

JO - Clinical Cancer Research

JF - Clinical Cancer Research

IS - 13

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Precision medicine approach to melanoma immunotherapy: Predicting response, adverse events, and hospital admissions using machine learning and explainable artificial intelligence

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