Literature DB >> 29664466

Points of Significance: Machine learning: a primer.

Danilo Bzdok1, Martin Krzywinski2, Naomi Altman3.   

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Year:  2017        PMID： 29664466      PMCID： PMC5905345          DOI： 10.1038/nmeth.4526

Source DB:  PubMed          Journal:  Nat Methods        ISSN： 1548-7091            Impact factor:   28.547


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  2 in total

1.  Sampling distributions and the bootstrap.

Authors:  Anthony Kulesa; Martin Krzywinski; Paul Blainey; Naomi Altman
Journal:  Nat Methods       Date:  2015-06       Impact factor: 28.547

Review 2.  Machine learning: Trends, perspectives, and prospects.

Authors:  M I Jordan; T M Mitchell
Journal:  Science       Date:  2015-07-17       Impact factor: 47.728
  2 in total
  21 in total

1.  Fluorescence spectral shape analysis for nucleotide identification.

Authors:  Yun Huang; Zhiliang Li; April L Risinger; Benjamin T Enslow; Charles J Zeman; Jiang Gong; Yajing Yang; Kirk S Schanze
Journal:  Proc Natl Acad Sci U S A       Date:  2019-07-15       Impact factor: 11.205

Review 2.  Machine Learning to Predict, Detect, and Intervene Older Adults Vulnerable for Adverse Drug Events in the Emergency Department.

Authors:  Kei Ouchi; Charlotta Lindvall; Peter R Chai; Edward W Boyer
Journal:  J Med Toxicol       Date:  2018-06-01

Review 3.  Machine learning approaches to study glioblastoma: A review of the last decade of applications.

Authors:  Jessica Valdebenito; Felipe Medina
Journal:  Cancer Rep (Hoboken)       Date:  2019-12

Review 4.  Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension.

Authors:  Chayakrit Krittanawong; Andrew S Bomback; Usman Baber; Sripal Bangalore; Franz H Messerli; W H Wilson Tang
Journal:  Curr Hypertens Rep       Date:  2018-07-06       Impact factor: 5.369

5.  From Hume to Wuhan: An Epistemological Journey on the Problem of Induction in COVID-19 Machine Learning Models and its Impact Upon Medical Research.

Authors:  Carlos Vega
Journal:  IEEE Access       Date:  2021-07-06       Impact factor: 3.367

6.  The ellipse of insignificance, a refined fragility index for ascertaining robustness of results in dichotomous outcome trials.

Authors:  David Robert Grimes
Journal:  Elife       Date:  2022-09-20       Impact factor: 8.713

7.  Statistics versus machine learning.

Authors:  Danilo Bzdok; Naomi Altman; Martin Krzywinski
Journal:  Nat Methods       Date:  2018-04-03       Impact factor: 28.547

8.  Machine Learning Algorithms to Differentiate Among Pulmonary Complications After Hematopoietic Cell Transplant.

Authors:  Husham Sharifi; Yu Kuang Lai; Henry Guo; Mita Hoppenfeld; Zachary D Guenther; Laura Johnston; Theresa Brondstetter; Laveena Chhatwani; Mark R Nicolls; Joe L Hsu
Journal:  Chest       Date:  2020-04-25       Impact factor: 10.262

9.  Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation.

Authors:  Shannon Wongvibulsin; Katherine C Wu; Scott L Zeger
Journal:  JMIR Med Inform       Date:  2020-06-09

10.  Longitudinal Connectomes as a Candidate Progression Marker for Prodromal Parkinson's Disease.

Authors:  Óscar Peña-Nogales; Timothy M Ellmore; Rodrigo de Luis-García; Jessika Suescun; Mya C Schiess; Luca Giancardo
Journal:  Front Neurosci       Date:  2019-01-09       Impact factor: 4.677
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