Artificial intelligence- image learning and its applications in neurooncology: a review Authors Malaika Javed Department of Surgery, Section of Neurosurgery, The Aga Khan University, Karachi, Pakistan. Mohammad Hamza Bajwa Department of Surgery, Section of Neurosurgery, The Aga Khan University, Karachi, Pakistan. Saqib Kamran Bakhshi Department of Surgery, Section of Neurosurgery, The Aga Khan University, Karachi, Pakistan. DOI: https://doi.org/10.47391/JPMA.AKU-9S-24 Abstract Image learning involves using artificial intelligence (AI) to analyse radiological images. Various machine and deeplearning- based techniques have been employed to process images and extract relevant features. These can later be used to detect tumours early and predict their survival based on their grading and classification. Radiomics is now also used to predict genetic mutations and differentiate between tumour progression and treatment-related side effects. These were once completely dependent on invasive procedures like biopsy and histopathology. The use and feasibility of these techniques are now widely being explored in neurooncology to devise more accurate management plans and limit morbidity and mortality. Continue... Downloads Full Text Article Published 2024-05-03 How to Cite Malaika Javed, Mohammad Hamza Bajwa, & Saqib Kamran Bakhshi. (2024). Artificial intelligence- image learning and its applications in neurooncology: a review. Journal of the Pakistan Medical Association, 74(4), S–158. https://doi.org/10.47391/JPMA.AKU-9S-24 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX Issue Vol. 74 No. 4 (2024): 9th AKU Annual Surgical Conference - Surgery In The Digital Era Section REVIEW ARTICLE License Copyright (c) 2024 Journal of the Pakistan Medical Association This work is licensed under a Creative Commons Attribution 4.0 International License.