Results 181 to 190 of about 61,068 (254)

Gradient boosting machine learning to improve satellite-derived column water vapor measurement error. [PDF]

Atmos Meas Tech, 2020
Just AC, Liu Y, Sorek-Hamer M, Rush J, Dorman M, Chatfield R, Wang Y, Lyapustin A, Kloog I.   +8 more
europepmc   +1 more source

Advancing the Design of High‐Efficiency Printable Hole‐Conductor‐Free Mesoscopic Perovskite Solar Cells Through Machine Learning

Advanced Science, EarlyView.
Based on the largest printable mesoscopic perovskite solar cells database we established, stacking model achieved precise PCE prediction (R2 = 0.73, MAE = 2.18%). Multiple experiments verified the accuracy of the model, which guided the fabrication of high‐PCE devices with an efficiency of 19.36%.
Hao Meng, Jingzi Zhang, Xu Zhu, Yuelin Wang, Antai Yang, Kailong Hu, Chengquan Zhong, Jiakai Liu, Menghan Dun, Xi Lin   +9 more
wiley   +1 more source

Cluster energy prediction based on multiple strategy fusion whale optimization algorithm and light gradient boosting machine. [PDF]

BMC Chem
Wei W, Mengshan L, Yan W, Lixin G.
europepmc   +1 more source

Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature

Advanced Science, EarlyView.
A deep learning model analyzes cfRNA profiles extracted from the blood of OVCA patients. This innovative approach distinguishes OVCA from healthy controls with high accuracy. Crucially, it reliably predicts patient response to chemotherapy (sensitive versus resistant subgroups).
Qinhao Guo, Yangyang Zhang, Yongcheng Jin, Siwei Deng, Yongqi Chen, Zheng Feng, Hao Wen, Liu Wang, Yilin Li, Fanghong Ou, Yong Shen, Haiming Li, Tianyao Zhou, Xingzhu Ju, Xiaohua Wu   +14 more
wiley   +1 more source

Non‐Noble Metal Nanocatalysts for Hydrogen Evolution

Advanced Science, EarlyView.
Recent overviews and latest developments of diverse classes of non‐noble catalysts for application toward high‐performance photocatalysis, thermocatalytic steam reforming, and electrocatalysis. Toward sustainability objectives, several advanced characterization tools in combination with the latest breakthroughs in machine learning for material ...
Lina Jaya Diguna, Gede Herry Arum Wijaya, Md Abdul Kuddus Sheikh, Tobias Haposan, Fidelis Stefanus Hubertson Simanjuntak, Arramel Arramel, Muhammad Danang Birowosuto, Konstantin Sergeevich Novoselov   +7 more
wiley   +1 more source

Machine‐Learning Framework for Designing Stable Interfaces in All‐Solid‐State Lithium‐Ion Batteries

Advanced Science, EarlyView.
A data‐driven strategy is developed to discover coating materials for all‐solid‐state lithium batteries. Using calculations of interfacial reactivity, unsupervised pattern recognition, and machine‐learning prediction, the study identifies low‐reactivity compositional patterns and screens new lithium‐based oxide and polyanion candidates, extending ...
Sehyeok Park, Myeongcho Jang, Hun‐Gi Jung, Kyung Yoon Chung, Seungho Yu   +4 more
wiley   +1 more source

Intrinsic Dual‐Phase Regulated GeSe2 Nanoparticles Triggered by Ball‐Milling Treatment for Photonic Multi‐Valued Logic Circuits

Advanced Science, EarlyView.
We report the solid‐state ball milling, a traditional, reliable, mass‐productive material processing, to prepare the air‐stable and dual‐phase GeSe2‐x nanoparticles with extended photodetection feasibility toward optical‐wavelength regions. We further display photonic multi‐valued logic (MVL) circuit through the employment of a hybrid PMMA/GeSe2‐x ...
An‐Ting Tsai, Chun‐Jen Wang, Pin‐Chao Liao, Chin Shan Lue, Chia‐Nung Kuo, Le Vo Phuong Thuan, Po‐Hsuan Hsiao, Chang‐Hyun Kim, Chia‐Yun Chen   +8 more
wiley   +1 more source

Deep Learning Network‐Tailored Microenvironment Matching of 4D Bioprinting Bioactive Scaffolds for Bone Regeneration

Advanced Science, EarlyView.
A DLN dataset was built to analyze MABS composition versus in vitro/in vivo osteogenesis and angiogenesis. An MLP neural network, taking BG morphological parameters as input, extracts bioactive features from these datasets. A rabbit tibial defect model then validates 4D‐printed MABS for adaptability and bone regeneration in critical defects.
Xiongjie Liang, Yuechi Zhang, Weifeng Hu, Shiyan Lv, Fan Jia, Yan Zhang, Feng Wu, Changjiang Yang, Guanqi Zhen, Jinglong Yan, Xu Cui, Wei Zhao, Guanghua Chen   +12 more
wiley   +1 more source

Sorption Behavior of Azo Dye Congo Red onto Activated Biochar from Haematoxylum campechianum Waste: Gradient Boosting Machine Learning-Assisted Bayesian Optimization for Improved Adsorption Process. [PDF]

Int J Mol Sci
Gamboa DMP, Abatal M, Lima E, Franseschi FA, Ucán CA, Tariq R, Elías MAR, Vargas J.   +7 more
europepmc   +1 more source

A Gradient Boosting Machine Learning Model for Predicting Early Mortality in the Emergency Department Triage: Devising a Nine-Point Triage Score. [PDF]

J Gen Intern Med, 2020
Klug M, Barash Y, Bechler S, Resheff YS, Tron T, Ironi A, Soffer S, Zimlichman E, Klang E.   +8 more
europepmc   +1 more source