Results 231 to 240 of about 741,105 (343)

Design of Single‐Atom Catalysts Anchored in N‐Doped Biphenylene Using Symbolic Regression for Electrocatalytic Nitrate Reduction to Ammonia

Advanced Science, EarlyView.
A high‐throughput in silico calculations for NO3RR based on transition metal doped and nitrogen decorated biphenylene network are performed. A symbolic regression is designed to capture the hidden descriptors of NO3RR for hyper dimensional system entailing large geometric variability.
Zheng Shu, Zhangsheng Shi, Huaxian Jia, Huifang Xu, Zian Xu, Zhongheng Li, Man‐Fai Ng, Teck Leong Tan, Fuqiang Huang, Yongqing Cai   +9 more
wiley   +1 more source

Artificial Intelligence in Obesity Prevention. [PDF]

Healthcare (Basel)
Shabani Jafarabadi G, Busetto L.
europepmc   +1 more source

Anthropometric determinants of change of direction speed in youth soccer players: A cross-sectional study using decision tree regression and machine learning approach

Akram Fray, Yassine Negra, Halil İbrahim Ceylan, Younés Hachana, Vаlentinа Ștefănică, Mevlüt YILDIZ, Ahmed Attia   +6 more
openalex   +1 more source

Decision-tree-based distributed learning for IoT devices [PDF]

Yui Yamashita, Akihito Taya, Takumi Wada, Yoshito Tobe   +3 more
openalex   +1 more source

Diffusion‐MRI‐Based Estimation of Cortical Architecture via Machine Learning (DECAM) in Primate Brains

Advanced Science, EarlyView.
We present Diffusion‐MRI‐based Estimation of Cortical Architecture via Machine Learning (DECAM), a deep‐learning framework for estimating primate brain cortical architecture optimized with best response constraint and cortical label vectors. Trained using macaque brain high‐resolution multi‐shell dMRI and histology data, DECAM generates high‐fidelity ...
Tianjia Zhu, Minhui Ouyang, Shufang Tan, Jianlin Guo, Ziqin Zhang, Xuan Liu, Risheng Liu, Hao Huang   +7 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

Integration of inter-simple sequence repeats with machine learning approach for diversity analysis and authentication of Iranian cotton cultivars. [PDF]

Biochem Biophys Rep
Hamid R, Ghorbanzadeh Z, Panahi B.
europepmc   +1 more source

Decision tree learning with hierarchical features

, 2018
The performance of machine learning methods depends on the data they are given. Real life data sets can be incomplete and consist of various types of data. However, many methods are capable of handling only nominal and numerical features without any missing data, which causes loss of potentially useful information.
openaire   +1 more source

Light Therapy Alleviates Addiction‐Related Symptoms and Reshapes Habenula and Midbrain Pathways

Advanced Science, EarlyView.
This study investigates light therapy for treating Internet Gaming Disorder (IGD). Functional MRI (fMRI) data reveal that light therapy enhances brain connectivity, particularly between the habenula and the medial orbitofrontal cortex (mOFC). These changes are associated with reduced withdrawal symptoms and addiction severity, highlighting the ...
Jinhui Li, Huiyang Huang, Cunhao Hu, Xuan Zhang, Song Lin, Xiaodan Huang, Ti‐fei Yuan, Kwok‐Fai So, Lu Huang, Chaoran Ren, Qian Tao   +10 more
wiley   +1 more source

Optimized ensemble machine learning model for cyberattack classification in industrial IoT. [PDF]

Front Artif Intell
Alabdullah B, Sankaranarayanan S.
europepmc   +1 more source