Results 131 to 140 of about 134,979 (307)

Practical Feature Subset Selection for Machine Learning

, 1998
Machine learning algorithms automatically extract knowledge from machine readable information. Unfortunately, their success is usually dependant on the quality of the data that they operate on.
Lloyd A. Smith, Hall, Mark A., Mark A. Hall, Smith, Lloyd A.   +3 more
core  

Spatial and Volumetric Characteristics of Glioblastoma: Associations With Clinical Presentation and Survival

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou, Marc Jaskir, Julian Gal, Yombe Fonkeu, Christos Davatzikos, MacLean P. Nasrallah, Jose Garcia, Rubo Xing, Stephen J. Bagley, Arati Desai, Richard E. Phillips, Steven Tobochnik, Colin A. Ellis, James J. Gugger, Nishant Sinha, Joel M. Stein, Kathryn A. Davis   +16 more
wiley   +1 more source

Comparison of Learning Outcomes Between Discovery Learning with Inquiry Learning Reviewed of Student Learning Independence At Vocational High School

, 2020
The provision of education provides a positive value for the development of the quality of Human Resources (HR), because global challenges and competition between nations in various aspects of life are increasingly competitive.
Ismawati, Rita, Rijanto, Tri, Lukitasari, Febriani, Nurlaela, Luthfiyah   +3 more
core  

Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig, Nadav Amir, Maya Schiller, Roni Loebenstein, Johnatan Nissan, Marina Boxer, Shany Guly Gofrit, Gal Goshen, Sándor Beniczky, Nicola Maggio   +9 more
wiley   +1 more source

Metabolic and Microvascular Risk Factors Associated With Brain Health in Type 1 Diabetes

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT We examined relationships between metabolic factors, microvascular complications, and brain health in adults with type 1 diabetes. Fifty‐one adults were assessed for metabolic risk factors, microvascular complications, and cognitive function, with a subset completing brain MRI.
Jihyun Park, Emily J. Koubek, Richard Beare, Lynn Ang, Brian C. Callaghan, Rodica Pop‐Busui, Eva L. Feldman, Evan L. Reynolds   +7 more
wiley   +1 more source

Kernel learning and optimization with Hilbert–Schmidt independence criterion

, 2017
© 2017, Springer-Verlag Berlin Heidelberg. Measures of statistical dependence between random variables have been successfully applied in many machine learning tasks, such as independent component analysis, feature selection, clustering and dimensionality
Wei Li, Li, W, Tinghua Wang, Wang, T
core   +1 more source

Evaluation of Digital Technologies for Home‐Based Assessment in People With Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller, Vanessa Vallejo, Mónica Povedano Panadés, Orla Hardiman, Véronique Danel‐Brunaud, Senda Ajroud‐Driss, Philippe Couratier, Jeremy Shefner, Anna Gokey, Mike DiCesare, Erin Lennox, Jens Praestgaard, Lucie Brujin, Peggy Allred, Ram Miller   +14 more
wiley   +1 more source

Quest for the Best: How to Measure Central Bank Independence and Show its Relationship with Inflation

The objective of this paper is to check measures for explanatory power of central bank independence (CBI) in a series of econometric tests. Measures of central bank autonomy offer a useful expression of the extent to which a central bank is able to keep ...
Aleksandra A. Maslowska
core  

Plasma EV Proteomics Identifies ECM Remodeling and Inflammatory Proteins LUM and C7 as Candidate Biomarkers in FSHD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit, Chiranth K. Nagaraj, Jackson S. Newell, Kim Truc Nguyen, Xilal Y. Rima, Jacob Doon‐Ralls, Eduardo Reátegui, Jeffrey M. Statland, Rabi Tawil, Kevin M. Flanigan, Scott Q. Harper, Nizar Y. Saad   +11 more
wiley   +1 more source

A 17 Year Old With Developmental Delay Presenting With Increasing Confusion and Imbalance

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Methylmalonic acidemia is an autosomal recessive genetic disorder primarily caused by defects in methylmalonyl‐CoA mutase and cobalamin (vitamin B12) metabolism. These defects disrupt the tricarboxylic acid cycle and oxidative phosphorylation, leading to the abnormal accumulation of metabolic products such as methylmalonic acid, propionic acid,
Wei Zhao, Yingli Zhang, Hongliang Zheng
wiley   +1 more source