Literature DB >> 31363197

Three pitfalls to avoid in machine learning.

Patrick Riley.   

Abstract

Keywords:  Mathematics and computing; Research data; Software

Mesh：

Year:  2019        PMID： 31363197     DOI： 10.1038/d41586-019-02307-y

Source DB:  PubMed          Journal:  Nature        ISSN： 0028-0836            Impact factor:   49.962


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  2 in total

1.  Achievement of Sustained Net Plasma Heating in a Fusion Experiment with the Optometrist Algorithm.

Authors:  E A Baltz; E Trask; M Binderbauer; M Dikovsky; H Gota; R Mendoza; J C Platt; P F Riley
Journal:  Sci Rep       Date:  2017-07-25       Impact factor: 4.379

2.  Learning data-driven discretizations for partial differential equations.

Authors:  Yohai Bar-Sinai; Stephan Hoyer; Jason Hickey; Michael P Brenner
Journal:  Proc Natl Acad Sci U S A       Date:  2019-07-16       Impact factor: 11.205
  2 in total
  18 in total

Review 1.  Artificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive data.

Authors:  Eleonora Inácio Fernandez; André Satoshi Ferreira; Matheus Henrique Miquelão Cecílio; Dóris Spinosa Chéles; Rebeca Colauto Milanezi de Souza; Marcelo Fábio Gouveia Nogueira; José Celso Rocha
Journal:  J Assist Reprod Genet       Date:  2020-07-11       Impact factor: 3.412

Review 2.  Application of machine learning in the management of acute myeloid leukemia: current practice and future prospects.

Authors:  Jan-Niklas Eckardt; Martin Bornhäuser; Karsten Wendt; Jan Moritz Middeke
Journal:  Blood Adv       Date:  2020-12-08

Review 3.  Artificial Intelligence Explained for Nonexperts.

Authors:  Narges Razavian; Florian Knoll; Krzysztof J Geras
Journal:  Semin Musculoskelet Radiol       Date:  2020-01-28       Impact factor: 1.777

4.  Data extraction methods for systematic review (semi)automation: A living systematic review.

Authors:  Lena Schmidt; Babatunde K Olorisade; Luke A McGuinness; James Thomas; Julian P T Higgins
Journal:  F1000Res       Date:  2021-05-19

5.  Multiscale modeling meets machine learning: What can we learn?

Authors:  Grace C Y Peng; Mark Alber; Adrian Buganza Tepole; William R Cannon; Suvranu De; Salvador Dura-Bernal; Krishna Garikipati; George Karniadakis; William W Lytton; Paris Perdikaris; Linda Petzold; Ellen Kuhl
Journal:  Arch Comput Methods Eng       Date:  2020-02-17       Impact factor: 7.302

6.  Facing small and biased data dilemma in drug discovery with enhanced federated learning approaches.

Authors:  Zhaoping Xiong; Ziqiang Cheng; Xinyuan Lin; Chi Xu; Xiaohong Liu; Dingyan Wang; Xiaomin Luo; Yong Zhang; Hualiang Jiang; Nan Qiao; Mingyue Zheng
Journal:  Sci China Life Sci       Date:  2021-07-26       Impact factor: 6.038

7.  Decoding and mapping task states of the human brain via deep learning.

Authors:  Xiaoxiao Wang; Xiao Liang; Zhoufan Jiang; Benedictor A Nguchu; Yawen Zhou; Yanming Wang; Huijuan Wang; Yu Li; Yuying Zhu; Feng Wu; Jia-Hong Gao; Bensheng Qiu
Journal:  Hum Brain Mapp       Date:  2019-12-09       Impact factor: 5.038

8.  Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments.

Authors:  Diego Morone; Alessandro Marazza; Timothy J Bergmann; Maurizio Molinari
Journal:  Mol Biol Cell       Date:  2020-05-13       Impact factor: 4.138

9.  Opportunities for Artificial Intelligence in Advancing Precision Medicine.

Authors:  Fabian V Filipp
Journal:  Curr Genet Med Rep       Date:  2019-12-01

10.  Machine learning models to predict length of stay and discharge destination in complex head and neck surgery.

Authors:  Khodayar Goshtasbi; Tyler M Yasaka; Mehdi Zandi-Toghani; Hamid R Djalilian; William B Armstrong; Tjoson Tjoa; Yarah M Haidar; Mehdi Abouzari
Journal:  Head Neck       Date:  2020-11-03       Impact factor: 3.147
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