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...
Guardado en:
Autores principales: | Chubin Ou, Jiahui Liu, Yi Qian, Winston Chong, Dangqi Liu, Xuying He, Xin Zhang, Chuan-Zhi Duan |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/72a0a387dcfb46f6aad06cd082ba06b4 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Thromboembolism during coiling of intracranial aneurysms: predictors and clinical outcome
por: Damian Kocur, et al.
Publicado: (2019) -
Deep learning based human activity recognition (HAR) using wearable sensor data
por: Saurabh Gupta
Publicado: (2021) -
Feasibility and efficacy of enhanced recovery after surgery protocol in Chinese elderly patients with intracranial aneurysm
por: Han H, et al.
Publicado: (2019) -
Morphological Irregularity of Unruptured Intracranial Aneurysms is More Related with Aneurysm Size Rather Than Cerebrovascular Atherosclerosis: A Case-Control Study
por: Qi P, et al.
Publicado: (2021) -
Underlying mechanism of hemodynamics and intracranial aneurysm
por: Haishuang Tang, et al.
Publicado: (2021)