Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis.

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Bibliographic Details
Title: Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis.
Authors: Akshay A; Functional Urology Research Group, Department for BioMedical Research DBMR, University of Bern, Switzerland.; Graduate School for Cellular and Biomedical Sciences, University of Bern, Switzerland., Katoch M; Institute of Neuropathology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany., Shekarchizadeh N; Department of Medical Data Science, Leipzig University Medical Centre, 04107 Leipzig, Germany.; Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) Dresden/Leipzig, 04105 Leipzig, Germany., Abedi M; Department of Medical Data Science, Leipzig University Medical Centre, 04107 Leipzig, Germany., Sharma A; KG Jebsen Centre for B-cell malignancies, Institute for Clinical Medicine, University of Oslo, Oslo, Norway.; Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway., Burkhard FC; Functional Urology Research Group, Department for BioMedical Research DBMR, University of Bern, Switzerland.; Department of Urology, Inselspital University Hospital, 3010 Bern, Switzerland., Adam RM; Urological Diseases Research Center, Boston Children's Hospital, MA, USA.; Harvard Medical School, Boston, Department of Surgery MA, USA.; Broad Institute of MIT and Harvard, Cambridge, MA, USA., Monastyrskaya K; Functional Urology Research Group, Department for BioMedical Research DBMR, University of Bern, Switzerland.; Department of Urology, Inselspital University Hospital, 3010 Bern, Switzerland., Gheinani AH; Functional Urology Research Group, Department for BioMedical Research DBMR, University of Bern, Switzerland.; Department of Urology, Inselspital University Hospital, 3010 Bern, Switzerland.; Urological Diseases Research Center, Boston Children's Hospital, MA, USA.; Harvard Medical School, Boston, Department of Surgery MA, USA.; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Source: BioRxiv : the preprint server for biology [bioRxiv] 2023 Jul 04. Date of Electronic Publication: 2023 Jul 04.
Publication Type: Preprint; Journal Article
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2692-8205
DOI:10.1101/2023.07.04.546825