Results 211 to 220 of about 9,750,100 (244)

Machine learning methods for gene regulatory network inference. [PDF]

Brief Bioinform
Hegde A, Nguyen T, Cheng J.
europepmc   +1 more source

Advances in Machine Learning for Mechanically Ventilated Patients. [PDF]

Int J Gen Med
Xu Y, Xue J, Deng Y, Tu L, Ding Y, Zhang Y, Yuan X, Xu K, Guo L, Gao N.   +9 more
europepmc   +1 more source

Machine learning for endoscopic third ventriculostomy success prediction-a systematic review and meta-analysis. [PDF]

Childs Nerv Syst
Łajczak A, Silva YP, Łajczak P.
europepmc   +1 more source

Machine learning- and multilayer molecular network-assisted screening hunts fentanyl compounds. [PDF]

Sci Adv
Shi C, Li W, Wang Y, Chen X, Yu M, Zhang H, You Z, Song M, Deng X, Fang M.   +9 more
europepmc   +1 more source

Predicting DNA origami stability in physiological media by machine learning

Zubia-Aranburu J, Gardin A, Paffen L, Tollemeto M, Alberdi A, Termenon M, Grisoni F, Patiño Padial T.   +7 more
europepmc   +1 more source

Machine Learning-Based Selection of Resection vs Transplant and Survival in Hepatocellular Carcinoma.

JAMA Netw Open
Kim HU, Han JW, Sung PS, Jang JW, Yoon SK, Choi HJ, You YK.   +6 more
europepmc   +1 more source

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Machine Learning Algorithms: A Review

International Journal of Science and Research (IJSR), 2022
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Ayon Dey
semanticscholar   +1 more source

Scikit-learn: Machine Learning in Python

Journal of machine learning research, 2011
Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.
Fabian Pedregosa, G. Varoquaux, Alexandre Gramfort, V. Michel, B. Thirion, O. Grisel, Mathieu Blondel, Gilles Louppe, P. Prettenhofer, Ron Weiss, Ron J. Weiss, J. Vanderplas, Alexandre Passos, D. Cournapeau, M. Brucher, M. Perrot, E. Duchesnay   +16 more
semanticscholar   +1 more source