Results 191 to 200 of about 90,198 (293)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Student-Centered Assessment Research on Holographic Learning Paradigm Based on Intelligent Analytic Hierarchy Process in Teaching of Bridge Engineering Course [PDF]

Maojun Duan, Fenghui Dong, Jiaqing Wang
openalex   +1 more source

Examining Faculty Dynamics in the Development of New Undergraduate Curricula that Transcend Disciplinary Silos. [PDF]

CBE Life Sci Educ
Frantz KJ, Lenhart CA, Bouwma-Gearhart J, Coffman CR.   +3 more
europepmc   +1 more source

Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Advanced Intelligent Discovery, EarlyView.
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki, Bassam Bachour Junior, Marcelo Mulato, José Ilton de Oliveira Filho   +3 more
wiley   +1 more source

The cost-analysis of Team-Based Learning versus small group interactive learning in undergraduate medical education. [PDF]

BMC Med Educ
Sterpu I, Herling L, Möller A, Kallner HK, Engberg H, Nordquist J, Acharya G.   +6 more
europepmc   +1 more source

Advances in Organic In‐Sensor Neuromorphic Computing: from Material Mechanisms to Applications

Advanced Intelligent Discovery, EarlyView.
This review discusses organic in‐sensor neuromorphic computing for wearable and bioelectronic systems, with a focus on memory‐based and OECT‐based synaptic devices. It highlights key design principles, recent advances, and existing challenges. By integrating sensing and processing within organic materials, the approach enables real‐time, low‐power, and
Dong Hyun Lee, Woojo Kim, Eun Kwang Lee, Hocheon Yoo   +3 more
wiley   +1 more source

Educational videos as a teaching approach to enhance dental students' practical skills in preclinical courses. [PDF]

BMC Med Educ
Dervisbegovic S, Laky M, Tur D, Grundnig J, Rausch-Fan X, Moritz A, Holzinger A.   +6 more
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Lessons Learned: Findings from an External Evaluation of a STEM Teaching and Learning Center (Lessons Learned Paper #2 of 2) [PDF]

Sarah Zappe, Deborah Jordan, Sam Spiegel, Megan Sanders, Stephanie Cutler   +4 more
openalex   +1 more source

Development and validation of the clinical educator self-regulated learning scale (CTSRS): insights from faculty development. [PDF]

BMC Med Educ
Wang SH, Chen YY, Hsieh MJ.
europepmc   +1 more source