Zobrazeno 1 - 10
of 1 409
pro vyhledávání: '"age prediction"'
Autor:
Nguyen Hai Thanh, Pham Linh Thuy Thi, Dang Dung Thi, Huynh Son Nguyen, Dang Phu Hao, Nguyen Quoc Thien Huynh
Publikováno v:
Applied Computer Systems, Vol 29, Iss 2, Pp 22-29 (2024)
Predicting age and gender through images is a common computer vision problem with many practical applications. However, this problem faces many difficulties because a person’s age can be affected by genetics, living environment, diet, health, gende
Externí odkaz:
https://doaj.org/article/6ae4a131666347b7a8a7ed5db180615a
Publikováno v:
Journal of Dental Sciences, Vol 19, Iss 4, Pp 1942-1950 (2024)
Background/purpose: The aim of this study was to determine the effects of age and sex on the difference between chronological age (CA) and dental age (DA) predicted using the Demirjian and Willems methods in Taiwanese children. Materials and methods:
Externí odkaz:
https://doaj.org/article/6dd9b812dfca4f869da2faf56bc3b018
Publikováno v:
Tomography, Vol 10, Iss 8, Pp 1238-1262 (2024)
The concept of ‘brain age’, derived from neuroimaging data, serves as a crucial biomarker reflecting cognitive vitality and neurodegenerative trajectories. In the past decade, machine learning (ML) and deep learning (DL) integration has transform
Externí odkaz:
https://doaj.org/article/db8bfa6b9a1f420bbd0f815ed4ffc87e
Autor:
Tommaso Ciceri, Letizia Squarcina, Alessandra Bertoldo, Paolo Brambilla, Simone Melzi, Denis Peruzzo
Publikováno v:
Frontiers in Pediatrics, Vol 12 (2024)
IntroductionGyrification is the intricate process through which the mammalian cerebral cortex develops its characteristic pattern of sulci and gyri. Monitoring gyrification provides valuable insights into brain development and identifies potential ab
Externí odkaz:
https://doaj.org/article/a85761dce70946e09d7b9181674bfbef
Publikováno v:
Frontiers in Neuroinformatics, Vol 18 (2024)
IntroductionOver the past few decades, numerous researchers have explored the application of machine learning for assessing children’s neurological development. Developmental changes in the brain could be utilized to gauge the alignment of its matu
Externí odkaz:
https://doaj.org/article/cc60188711404a9b80099461a91ac5fc
Autor:
Catharina J. A. Romme, Emma A. M. Stanley, Pauline Mouches, Matthias Wilms, G. Bruce Pike, Luanne M. Metz, Nils D. Forkert
Publikováno v:
Frontiers in Neurology, Vol 15 (2024)
IntroductionThe rate of neurodegeneration in multiple sclerosis (MS) is an important biomarker for disease progression but can be challenging to quantify. The brain age gap, which quantifies the difference between a patient's chronological and their
Externí odkaz:
https://doaj.org/article/401f983d703e4c49923d99c9f040be23
Autor:
Xiaotong Wu, Chenxin Xie, Fangxiao Cheng, Zhuoshuo Li, Ruizhuo Li, Duan Xu, Hosung Kim, Jianjia Zhang, Hongsheng Liu, Mengting Liu
Publikováno v:
NeuroImage, Vol 300, Iss , Pp 120861- (2024)
Significant changes in brain morphology occur during the third trimester of gestation. The capability of deep learning in leveraging these morphological features has enhanced the accuracy of brain age predictions for this critical period. Yet, the op
Externí odkaz:
https://doaj.org/article/c7793c462591455596442adfcc96f769
Publikováno v:
NeuroImage, Vol 299, Iss , Pp 120806- (2024)
Recent studies indicate that differences in cognition among individuals may be partially attributed to unique brain wiring patterns. While functional connectivity (FC)-based fingerprinting has demonstrated high accuracy in identifying adults, early s
Externí odkaz:
https://doaj.org/article/da8faa0f86d943ac80099d074f332209
Autor:
Zhicong Fang, Ningning Pan, Shujuan Liu, Hongzhuang Li, Minmin Pan, Jiong Zhang, Zhuoshuo Li, Mengting Liu, Xinting Ge
Publikováno v:
NeuroImage, Vol 299, Iss , Pp 120815- (2024)
Using machine learning techniques to predict brain age from multimodal data has become a crucial biomarker for assessing brain development. Among various types of brain imaging data, structural magnetic resonance imaging (sMRI) and diffusion magnetic
Externí odkaz:
https://doaj.org/article/5ef7cb3653884571ad2abff1b40100b9
Publikováno v:
NeuroImage, Vol 299, Iss , Pp 120825- (2024)
As an important biomarker of neural aging, the brain age reflects the integrity and health of the human brain. Accurate prediction of brain age could help to understand the underlying mechanism of neural aging. In this study, a cross-stratified ensem
Externí odkaz:
https://doaj.org/article/f4aa1d75c32c441a8766d4c61c04d731