Results 161 to 170 of about 13,565 (211)

Targeting WDR12 Unleashes T‐Cell‐Mediated Antitumor Activity in Melanoma by Destabilizing CD276

Advanced Science, EarlyView.
WDR12 cooperates with the chaperonin subunit CCT7 to maintain CD276 stability on tumor cells, suppressing T‐cell activity and promoting immune escape. SU14813, a small‐molecule WDR12 inhibitor, reduces CD276 stability and relieves CD276‐mediated T‐cell suppression.
Jie Pan, Ruimin Chang, Meng Zhang, Qian Dong, Guanxiong Zhang, Xiang Chen, Mingliang Chen, Lixia Lu, Xiaowei Liang, Yeye Guo, Juan Su   +10 more
wiley   +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

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

Application of the Random Forest Method for Classifying Diabetes

Eka Putri Yuniarsih, Mutia Nur Estri, Najmah Istikaanah, Idha Sihwaningrum   +3 more
openaire   +1 more source

Programmable Multi‐Axially Aligned Aerogels via Sequential Freeze‐Casting for Tailored Anisotropy and Tunable Mechanics

Advanced Science, EarlyView.
Conventional single‐gradient freeze‐casting typically produces unidirectional porous architectures with limited transverse connectivity. The Sequential Hybridization by Infiltration and Freeze‐casting Technique (SHIFT) addresses this constraint by integrating secondary aligned structures within a preformed primary scaffold.
Kiho Sung, Sungchul Shin
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

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Combination methods in a Fuzzy Random Forest

2008 IEEE International Conference on Systems, Man and Cybernetics, 2008
When individual classifiers are combined appropriately, we usually obtain a better performance in terms of classification precision. Multi-classifiers are the result of combining several individual classifiers. In this work we propose and compare various combination methods to obtain the final decision of the multi-classifier based on a ...
Piero P. Bonissone, José Manuel Cadenas, María del Carmen Garrido, Ramon Andrés Díaz-Valladares   +3 more
openaire   +1 more source

BiMM forest: A random forest method for modeling clustered and longitudinal binary outcomes

Chemometrics and Intelligent Laboratory Systems, 2019
Clustered binary outcomes and datasets with many predictor variables are frequently encountered in clinical research (e.g. longitudinal studies). Generalized linear mixed models (GLMMs) typically employed for clustered endpoints have challenges for some scenarios, particularly for complex datasets which contain many interactions among predictors and ...
Karvellas Cj, Bethany Wolf, Dongjun Chung   +2 more
exaly   +4 more sources

Random Forest and Ensemble Methods

2020
Recent expansions of technology led to growth and availability of different types of data. This, thus gave various opportunities for the machine learning, data mining, chemometrics and data science fields. Both fields have been consequently developing new approaches and algorithms in a wide range of applications in biomedical, medical, -omics but also ...
Stavropoulos, George, van Vorstenbosch, Robert, van Schooten, Frederik, Blanchet - Smolinska, Agnieszka   +3 more
openaire   +2 more sources