Automated Machine Learning Model Development for Intracranial Aneurysm Treatment Outcome Prediction: A Feasibility Study
Background: The prediction of aneurysm treatment outcomes can help to optimize the treatment strategies. Machine learning (ML) has shown positive results in many clinical areas. However, the development of such models requires expertise in ML, which is not an easy task for surgeons.Objectives: The r...
Enregistré dans:
Auteurs principaux: | Chubin Ou, Jiahui Liu, Yi Qian, Winston Chong, Dangqi Liu, Xuying He, Xin Zhang, Chuan-Zhi Duan |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Frontiers Media S.A.
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/72a0a387dcfb46f6aad06cd082ba06b4 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Thromboembolism during coiling of intracranial aneurysms: predictors and clinical outcome
par: Damian Kocur, et autres
Publié: (2019) -
Deep learning based human activity recognition (HAR) using wearable sensor data
par: Saurabh Gupta
Publié: (2021) -
Feasibility and efficacy of enhanced recovery after surgery protocol in Chinese elderly patients with intracranial aneurysm
par: Han H, et autres
Publié: (2019) -
Morphological Irregularity of Unruptured Intracranial Aneurysms is More Related with Aneurysm Size Rather Than Cerebrovascular Atherosclerosis: A Case-Control Study
par: Qi P, et autres
Publié: (2021) -
Underlying mechanism of hemodynamics and intracranial aneurysm
par: Haishuang Tang, et autres
Publié: (2021)