Results 181 to 190 of about 7,605,221 (315)

Meaningful learning with technology

Journal of Open, Flexible and Distance Learning, 2023
openaire   +3 more sources

Ecologically‐Valid Emotion Signatures Enhance Mood Disorder Diagnostics

Advanced Science, EarlyView.
This study identifies ecologically‐valid Divergent Emotional Functional Networks (DEFN), derived from dynamic functional connectivity during naturalistic movie watching. The DEFN reliably enhances diagnostic accuracy for mood disorders, including major depressive and bipolar disorders, demonstrating strong reproducibility across demographic factors and
Shuyue Xu, Linling Li, Ting Luo, Gan Huang, Li Zhang, Benjamin Becker, Zhen Liang   +6 more
wiley   +1 more source

Educational action to monitor children's growth and development based on the theory of meaningful learning. [PDF]

Rev Esc Enferm USP
Vieira DS, Brito PKH, Bezerra ICDS, Soares AR, Santos LMD, Toso BRGO, Vaz EMC, Collet N, Reichert APDS.   +8 more
europepmc   +1 more source

Data‐Driven Printability Modeling of Hydrogels for Precise Direct Ink Writing Based on Rheological Properties

Advanced Science, EarlyView.
A predictive model for 3D printability is developed by integrating rheological analysis, including the Large Amplitude Oscillatory Shear (LAOS) test, with machine learning. With prediction errors under 10%, the model shows that post‐extrusion recovery controls horizontal printability, while high‐strain‐rate nozzle flow dictates vertical printability ...
Eun Hui Jeong, Jiho Choi, Han Bi Park, Ji Woo Lee, Seo Yeon Bae, Byoung Soo Kim, ChangKyu Yoon, Jun Dong Park   +7 more
wiley   +1 more source

CLinNET: An Interpretable and Uncertainty‐Aware Deep Learning Framework for Multi‐Modal Clinical Genomics

Advanced Science, EarlyView.
Identifying disease‐causing genes in neurocognitive disorders remains challenging due to variants of uncertain significance. CLinNET employs dual‐branch neural networks integrating Reactome pathways and Gene Ontology terms to provide pathway‐level interpretability of genomic alterations.
Ivan Bakhshayeshi, Mohammad Mahdi Hosseini, Ahmadreza Argha, Roxana Zahedi, Nigel H. Lovell, Hamid Alinejad‐Rokny   +5 more
wiley   +1 more source

Assessing the Relative Importance of Imaging and Serum Biomarkers in Capturing Disability, Cognitive Impairment, and Clinical Progression in Multiple Sclerosis

Advanced Science, EarlyView.
Using machine‐learning analyses in two independent multiple sclerosis cohorts, spinal cord atrophy and cortical degeneration emerged as key predictors of disability and progression independent of relapses. Deep gray matter damage further improved prediction, while serum biomarkers of brain damage provided complementary information, highlighting the ...
Alessandro Cagol, Pascal Benkert, Sabine Schaedelin, Mario Ocampo‐Pineda, Noemi Montobbio, Po‐Jui Lu, Batuhan Ayci, Antonia Wenger, Alfi Aran Shukur, Kornelius Kaim, Lester Melie‐Garcia, Matthias Weigel, Alessio Signori, Pasquale Calabrese, Ludwig Kappos, Maria Pia Sormani, Jens Kuhle, Cristina Granziera   +17 more
wiley   +1 more source

DualPG‐DTA: A Large Language Model‐Powered Graph Neural Network Framework for Enhanced Drug‐Target Affinity Prediction and Discovery of Novel CDK9 Inhibitors Exhibiting in Vivo Anti‐Leukemia Activity

Advanced Science, EarlyView.
This study introduces DualPG‐DTA, a framework integrating two pre‐trained models to generate molecular and protein representations. It constructs dual graphs processed by specialized neural networks with dynamic attention for feature fusion, achieving superior benchmark performance.
Yihao Chen, Jindi Huang, Cong Liu, Shipeng Zhang, Xinze Li, Zhang Zhang, Tie‐Gen Chen, Ling Wang   +7 more
wiley   +1 more source

Aprendizaje significativo crítico (Critical meaningful learning)

Indivisa, Boletín de Estudios e Investigación, 2005
Moreira Marco Antonio
doaj  

Declaring Worldviews in SSM for Sustainability & Community Learning. [PDF]

Syst Pract Action Res
Weaver MW, Herron RJM, Pokorna K, Salinas Navarro DE, Vilalta-Perdomo E.   +4 more
europepmc   +1 more source

Comment on “De Novo Reconstruction of 3D Human Facial Images from DNA Sequence”

Advanced Science, EarlyView.
This comment examines AI‐driven DNA‐based facial reconstruction, focusing on the Difface model. While such technologies promise biomedical and forensic applications, they pose significant ethical, legal, and methodological challenges. We emphasize transparency, benchmarking, and rigorous validation to avoid misinterpretation and misuse.
Jennifer K. Wagner, Nina Claessens, Caitlin M. Maloney, Peter Claes   +3 more
wiley   +1 more source