Application of Artificial Intelligence in Diagnosis of Craniopharyngioma
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Craniopharyngioma is a congenital brain tumor with clinical characteristics of hypothalamic-pituitary dysfunction, increased intracranial pressure, and visual field disorder, among other injuries. Its clinical diagnosis mainly depends on radiological examinations (such as Computed Tomography, Magnetic Resonance Imaging). However, assessing numerous radiological images manually is a challenging task, and the experience of doctors has a great influence on the diagnosis result. The development of artificial intelligence has brought about a great transformation in the clinical diagnosis of craniopharyngioma. This study reviewed the application of artificial intelligence technology in the clinical diagnosis of craniopharyngioma from the aspects of differential classification, prediction of tissue invasion and gene mutation, prognosis prediction, and so on. Based on the reviews, the technical route of intelligent diagnosis based on the traditional machine learning model and deep learning model were further proposed. Additionally, in terms of the limitations and possibilities of the development of artificial intelligence in craniopharyngioma diagnosis, this study discussed the attentions required in future research, including few-shot learning, imbalanced data set, semi-supervised models, and multi-omics fusion.
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Harary P, Rajaram S, Hori Y, Park D, Chang S J Neurooncol. 2025; .
PMID: 40063185 DOI: 10.1007/s11060-025-05001-4.
Javidialsaadi M, Luy D, Smith H, Cecia A, Yang S, Germanwala A J Clin Med. 2025; 14(4).
PMID: 40004632 PMC: 11856613. DOI: 10.3390/jcm14041101.
Artificial Intelligence for Neuroimaging in Pediatric Cancer.
Dalboni da Rocha J, Lai J, Pandey P, Myat P, Loschinskey Z, Bag A Cancers (Basel). 2025; 17(4).
PMID: 40002217 PMC: 11852968. DOI: 10.3390/cancers17040622.
Patel K, Sanghvi H, Gill G, Agarwal O, Pandya A, Agarwal A Cureus. 2025; 16(12):e75476.
PMID: 39791061 PMC: 11717160. DOI: 10.7759/cureus.75476.
Calandrelli R, DApolito G, Martucci M, Giordano C, Schiarelli C, Marziali G Cancers (Basel). 2024; 16(14).
PMID: 39061172 PMC: 11275213. DOI: 10.3390/cancers16142532.