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Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview

Intracranial aneurysms (IAs) are a significant public health concern. In populations without comorbidity and a mean age of 50 years, their prevalence is up to 3.2%. An efficient method for identifying subjects at high risk of an IA is warranted to provide adequate radiological screening guidelines a...

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Autores principales: Marasini, Anurag, Shrestha, Alisha, Phuyal, Subash, Zaidat, Osama O., Kalia, Junaid Siddiq
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904392/
https://www.ncbi.nlm.nih.gov/pubmed/35280303
http://dx.doi.org/10.3389/fneur.2022.784326
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author Marasini, Anurag
Shrestha, Alisha
Phuyal, Subash
Zaidat, Osama O.
Kalia, Junaid Siddiq
author_facet Marasini, Anurag
Shrestha, Alisha
Phuyal, Subash
Zaidat, Osama O.
Kalia, Junaid Siddiq
author_sort Marasini, Anurag
collection PubMed
description Intracranial aneurysms (IAs) are a significant public health concern. In populations without comorbidity and a mean age of 50 years, their prevalence is up to 3.2%. An efficient method for identifying subjects at high risk of an IA is warranted to provide adequate radiological screening guidelines and effectively allocate medical resources. Artificial intelligence (AI) has received worldwide attention for its impressive performance in image-based tasks. It can serve as an adjunct to physicians in clinical settings, improving diagnostic accuracy while reducing physicians' workload. AI can perform tasks such as pattern recognition, object identification, and problem resolution with human-like intelligence. Based on the data collected for training, AI can assist in decisions in a semi-autonomous manner. Similarly, AI can identify a likely diagnosis and also, select a suitable treatment based on health records or imaging data without any explicit programming (instruction set). Aneurysm rupture prediction is the holy grail of prediction modeling. AI can significantly improve rupture prediction, saving lives and limbs in the process. Nowadays, deep learning (DL) has shown significant potential in accurately detecting lesions on medical imaging and has reached, or perhaps surpassed, an expert-level of diagnosis. This is the first step to accurately diagnose UIAs with increased computational radiomicis. This will not only allow diagnosis but also suggest a treatment course. In the future, we will see an increasing role of AI in both the diagnosis and management of IAs.
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spelling pubmed-89043922022-03-10 Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview Marasini, Anurag Shrestha, Alisha Phuyal, Subash Zaidat, Osama O. Kalia, Junaid Siddiq Front Neurol Neurology Intracranial aneurysms (IAs) are a significant public health concern. In populations without comorbidity and a mean age of 50 years, their prevalence is up to 3.2%. An efficient method for identifying subjects at high risk of an IA is warranted to provide adequate radiological screening guidelines and effectively allocate medical resources. Artificial intelligence (AI) has received worldwide attention for its impressive performance in image-based tasks. It can serve as an adjunct to physicians in clinical settings, improving diagnostic accuracy while reducing physicians' workload. AI can perform tasks such as pattern recognition, object identification, and problem resolution with human-like intelligence. Based on the data collected for training, AI can assist in decisions in a semi-autonomous manner. Similarly, AI can identify a likely diagnosis and also, select a suitable treatment based on health records or imaging data without any explicit programming (instruction set). Aneurysm rupture prediction is the holy grail of prediction modeling. AI can significantly improve rupture prediction, saving lives and limbs in the process. Nowadays, deep learning (DL) has shown significant potential in accurately detecting lesions on medical imaging and has reached, or perhaps surpassed, an expert-level of diagnosis. This is the first step to accurately diagnose UIAs with increased computational radiomicis. This will not only allow diagnosis but also suggest a treatment course. In the future, we will see an increasing role of AI in both the diagnosis and management of IAs. Frontiers Media S.A. 2022-02-23 /pmc/articles/PMC8904392/ /pubmed/35280303 http://dx.doi.org/10.3389/fneur.2022.784326 Text en Copyright © 2022 Marasini, Shrestha, Phuyal, Zaidat and Kalia. 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
Marasini, Anurag
Shrestha, Alisha
Phuyal, Subash
Zaidat, Osama O.
Kalia, Junaid Siddiq
Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview
title Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview
title_full Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview
title_fullStr Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview
title_full_unstemmed Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview
title_short Role of Artificial Intelligence in Unruptured Intracranial Aneurysm: An Overview
title_sort role of artificial intelligence in unruptured intracranial aneurysm: an overview
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8904392/
https://www.ncbi.nlm.nih.gov/pubmed/35280303
http://dx.doi.org/10.3389/fneur.2022.784326
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