Artificial intelligence- image learning and its applications in neurooncology: a review.

J Pak Med Assoc

Department of Surgery, Section of Neurosurgery, The Aga Khan University, Karachi, Pakistan.

Published: April 2024

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. Hence, the future of oncology lies in the exploration of AI-based image learning techniques, which can be applied to formulate management plans based on less invasive diagnostic techniques, earlier detection of tumours, and prediction of prognosis based on radiomic features. In this review, we discuss some of these applications of image learning in current medical dynamics.

Download full-text PDF

Source
http://dx.doi.org/10.47391/JPMA.AKU-9S-24DOI Listing

Publication Analysis

Top Keywords

image learning
16
management plans
8
artificial intelligence-
4
image
4
intelligence- image
4
learning
4
learning applications
4
applications neurooncology
4
neurooncology review
4
review image
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!