Results 201 to 210 of about 5,782,720 (331)

CAMELLIA: an alignment-free pipeline integrating <i>k</i>-mer feature selection and supervised classification for genomic sequence subtyping. [PDF]

NAR Genom Bioinform
Saita TM, Pimenta-Zanon MH, de Queiroz ATL, Bressan GM, Lopes FM.   +4 more
europepmc   +1 more source

White Matter Microstructural Abnormalities in Neonatal Onset Genetic Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Recent evidence indicates that epilepsy is associated with abnormal white matter. If seizures alter white matter, then the impact upon network function, epileptogenesis, and cognition could be pronounced in neonates undergoing rapid developmental myelination. Neonates with epilepsy due to nonstructural genetic causes provide a unique
Amanda G. Sandoval Karamian, Tianjia Zhu, Hao Huang, Shavonne L. Massey, Mark P. Fitzgerald, Darshana Parikh, Arastoo Vossough, Ingo Helbig, Nicholas S. Abend   +8 more
wiley   +1 more source

Enhancing strawberry maturity assessment using mid-infrared spectral analysis with advanced variable selection and supervised classification. [PDF]

Sci Rep
Rammal A, Assaf R, Perrin E, Vrabie V.
europepmc   +1 more source

Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane, Valentina Giunchiglia, Michael C. B. David, Magdalena A. Kolanko, William R. Trender, Peter J. Hellyer, Harmeena Kaur, David J. Sharp, Christopher Carswell, Paresh A. Malhotra, Adam Hampshire   +10 more
wiley   +1 more source

Development and optimization of a morphodiversity model for mountainous areas using supervised classification and artificial neural networks. [PDF]

Sci Rep
Bartuś T.
europepmc   +1 more source

Supervised Data Classification via Max-min Separability

, 2005
Supervised Data Classification via Max-min ...
Julien Ugon (13077438), Adil M Bagirov (19465882)   +1 more
core  

Upper Cervical Cord Area as a Biomarker of Conversion to Secondary Progressive Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective This study assessed whether upper cervical cord area (UCCA) measured on routine brain MRI can serve as a biomarker of conversion to SPMS. Methods This is a single‐center retrospective cohort study of RRMS patients with cross‐sectional and longitudinal analyses of clinical and MRI data. Future SPMS converters were matched by age, sex,
Nabil K. El Ayoubi, Sola Al Ghazal, Salem Hannoun, Medhat A. Siddik, Nour M. Najjar, Jim Dagher, Joseph Abboud, Myriam G. Semaan, Samia J. Khoury   +8 more
wiley   +1 more source

[Self-supervised classification method for breast pathology images fusing geometric priors and multi-scale attention]. [PDF]

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
Jiang L, Cao H, Nie Y, Zhang C.
europepmc   +1 more source

Clinical and Modifiable Factors Associated With Disability and Relapse in MOGAD: A Multicentre Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Factors associated with relapse course and disability in myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD) remain incompletely understood. Objectives To identify clinical and modifiable factors associated with relapse and disability in MOGAD. Methods In this ambispective multicentre cohort study using data from
Yingtao Wang, Shaoxin Tao, Qiujia Wang, Xiaoyu Xu, Hui Yao, Zheng Liu, Dawei Li, Zhandong Qiu, Jinming Han, Jiangwei Xia, Qi Wang, Jun Sun, Kai Shao, Jiao Li, Shishuang Ruan, Yi Zhong, Jun Guo, Shougang Guo, Yue Huang, Guoliang Chai, Tao Jin, Hongyu Zhou, Junwei Hao, Yinan Zhao   +23 more
wiley   +1 more source

Policy Learning for Actively Labeled Sample Selection on Lumbar Semi-supervised Classification. [PDF]

J Imaging Inform Med
Hai J, Chen J, Qiao K, Su Z, Lu H, Yan B.   +5 more
europepmc   +1 more source