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Application of Artificial Intelligence in Diagnosis of Craniopharyngioma
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, Magnet...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8770750/ https://www.ncbi.nlm.nih.gov/pubmed/35069406 http://dx.doi.org/10.3389/fneur.2021.752119 |
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author | Qin, Caijie Hu, Wenxing Wang, Xinsheng Ma, Xibo |
author_facet | Qin, Caijie Hu, Wenxing Wang, Xinsheng Ma, Xibo |
author_sort | Qin, Caijie |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8770750 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87707502022-01-21 Application of Artificial Intelligence in Diagnosis of Craniopharyngioma Qin, Caijie Hu, Wenxing Wang, Xinsheng Ma, Xibo Front Neurol Neurology 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. Frontiers Media S.A. 2022-01-06 /pmc/articles/PMC8770750/ /pubmed/35069406 http://dx.doi.org/10.3389/fneur.2021.752119 Text en Copyright © 2022 Qin, Hu, Wang and Ma. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Qin, Caijie Hu, Wenxing Wang, Xinsheng Ma, Xibo Application of Artificial Intelligence in Diagnosis of Craniopharyngioma |
title | Application of Artificial Intelligence in Diagnosis of Craniopharyngioma |
title_full | Application of Artificial Intelligence in Diagnosis of Craniopharyngioma |
title_fullStr | Application of Artificial Intelligence in Diagnosis of Craniopharyngioma |
title_full_unstemmed | Application of Artificial Intelligence in Diagnosis of Craniopharyngioma |
title_short | Application of Artificial Intelligence in Diagnosis of Craniopharyngioma |
title_sort | application of artificial intelligence in diagnosis of craniopharyngioma |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8770750/ https://www.ncbi.nlm.nih.gov/pubmed/35069406 http://dx.doi.org/10.3389/fneur.2021.752119 |
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