Results 41 to 50 of about 299,509 (268)

Self‐Regulated Learning Meets AI: Reinterpreting Self‐Regulation, Co‐Regulation, and Socially Shared Regulation in Human–AI Interaction

open access: yesNew Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley   +1 more source

A scalable hybrid recommendation framework for e-commerce using distributed big data processing

open access: yesDiscover Computing
The online retail platforms of the last decade have gone through an exponential expansion, with Amazon being a prime example. This expansion has resulted in the generation of a vast amount of user–product interaction data, which traditional single-node ...
Sahil Goyal   +5 more
doaj   +1 more source

UrbanBlocks 3-D: A Genetic Algorithm-Based Semantic Zoning Framework for Smart Cities

open access: yesIEEE Access
Urban planning faces critical challenges with 68% of the global population projected to live in cities by 2050, requiring intelligent zoning solutions for sustainable development.
Somesh Nandi   +3 more
doaj   +1 more source

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

open access: yesAnnals 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   +16 more
wiley   +1 more source

PolarBearVidID: A Video-Based Re-Identification Benchmark Dataset for Polar Bears

open access: yesAnimals, 2023
Automated monitoring systems have become increasingly important for zoological institutions in the study of their animals’ behavior. One crucial processing step for such a system is the re-identification of individuals when using multiple cameras.
Matthias Zuerl   +8 more
doaj   +1 more source

A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi   +17 more
wiley   +1 more source

Thalamo‐Lesional Connectivity Signatures of Bilateral Tonic–Clonic Seizures in Focal Cortical Dysplasia‐Related Epilepsy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie   +8 more
wiley   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

Probabilistic machine learning and artificial intelligence [PDF]

open access: yesNature, 2015
How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience.
openaire   +3 more sources

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

open access: yesArthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah   +4 more
wiley   +1 more source

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