Results 121 to 130 of about 522,455 (311)

Efficient reduction of computational complexity in video surveillance using hybrid machine learning for event recognition

This paper addresses the challenge of high computational complexity in video surveillance systems by proposing an efficient model that integrates hybrid machine learning algorithms (HML) for event recognition.
Mallikarjunaiah, Komala, Honnegowda, Jyothi, Srikantaswamy, Mallikarjunaswamy   +2 more
core   +1 more source

Machine-Learning-Guided Discovery of Electrochemical Reactions

, 2022
The molecular structures synthesizable by organic chemists dictate the molecular functions they can create. The invention and development of chemical reactions are thus critical for chemists to access new and desirable functional molecules in all ...
Ron Shprints (14209527), Esther Heid (4497256), Klavs F. Jensen (722008), Andrew F. Zahrt (8196378), Yiming Mo (6065171), Kakasaheb Y. Nandiwale (6069704)   +5 more
core   +1 more source

Coarse-grained machine learning potential for mesoscale multilayered graphene

npj Computational Materials
A coarse-grained neuroevolution potential (CGNEP) for multilayered graphene based on an ab initio accuracy dataset is developed for mesoscale molecular dynamics simulations.
Mingqian Li, Lifeng Wang, Zhuoqun Zheng
doaj   +1 more source

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

Machine learning and complex biological data

Genome Biology, 2019
Machine learning has demonstrated potential in analyzing large, complex biological data. In practice, however, biological information is required in addition to machine learning for successful application.
Chunming Xu, Scott A. Jackson
doaj   +1 more source

Longitudinal Assessment of Biomarkers in ALS: Discriminative Biomarkers for Disease Progression and Survival

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the association and discriminative performance of serum biomarkers with clinical disease progression and survival in patients with amyotrophic lateral sclerosis (ALS). Methods This retrospective study, conducted at Houston Methodist Hospital, Houston, TX, used longitudinal serum samples collected between January 2018 and ...
David R. Beers, Yueh‐Yun Lin, Jason R. Thonhoff, Aaron D. Thome, Alireza Faridar, Weihua Zhao, Shixiang Wen, Stanley H. Appel   +7 more
wiley   +1 more source

Machine learning based modeling for estimating solar power generation [PDF]

E3S Web of Conferences
The solar power plant is a rapidly growing renewable energy source that has a potential role in reducing climate change and replacing fossil fuels.
Uddin Nur, Purwanto Edi, Nugraha Hari
doaj   +1 more source

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects

Predictive maintenance is an essential aspect of microgrid operations as it enables identifying potential equipment failures in advance, reducing downtime, and increasing the overall efficiency of the system.
Arafat, MY, Hossain, MJ, Alam, MM
core   +1 more source

Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP [PDF]

, 2018
During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses.
Schmid, Ute, Tamaddoni-Nezhad, A, Zeller, C, Tamaddoni-Nezhad, A., Ute Schmid, Muggleton, SH, Tamaddoni-Nezhad, Alireza, Alireza Tamaddoni-Nezhad, Muggleton, Stephen H., Besold, Tarek, Christina Zeller, Muggleton, Stephen, Zeller, C., Schmid, U, Schmid, U., Besold, T, Zeller, Christina, Tarek Besold, Stephen H. Muggleton, Besold, T. R., Muggleton, S.   +20 more
core   +1 more source