Author

Milind Y. Desai

Cleveland ClinicORCID 0000-0003-0010-9797Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexander BartholomäusiD· 1 shared Alexander DiltheyiD· 1 shared Alexander GoesmanniD· 1 shared Andreas DiefenbachiD· 1 shared Andreas KelleriD· 1 shared Angel AngeloviD· 1 shared Anke BeckeriD· 1 shared Anna C. AschenbrenneriD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperBioinformatics

Alexander BartholomäusORCID

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2 papers

Recent·Most cited

Genotype-Phenotype Correlations Identify Phenotypic Differences in Sarcomere Mutation-Positive Hypertrophic Cardiomyopathy in the NHLBI HCM Registry

Jonathan Chan, Christopher Grace, Kate L. Thomson, Dong‐Yun Kim, Patrice M. Desvigne-Nickens, Paul Kolm, John P. DiMarco, Milind Y. Desai, Raymond Y.K. Kwong, Carolyn Yung Ho, William S. Weintraub, Stefan Neubauer, Christopher M. Kramer, Hugh C Watkins, Anuj Goel

The paper identifies phenotypic differences in sarcomere mutation-positive hypertrophic cardiomyopathy using CMR data from the NHLBI HCM Registry, resolving prior discrepancies through meta-analysis.

medRxiv · Jul 30, 2026 · PreprintGenetic & Genomic Medicine

Swarm Learning as a privacy-preserving machine learning approach for disease classification

Stefanie Warnat‐Herresthal, Hartmut Schultze, Krishnaprasad Shastry, Sathyanarayanan Manamohan, Saikat Mukherjee, Vishesh Garg, Ravi Sarveswara, Kristian Händler, Peter Pickkers, N. Ahmad Aziz, Sofia Ira Ktena, Florian Tran, Michael Bitzer, Stephan Ossowski, Nicolas Casadei, , Alexander Goesmann

This paper introduces Swarm Learning, a decentralized machine learning approach for disease classification using transcriptomic data, demonstrating its effectiveness in developing classifiers for COVID-19, tuberculosis, and leukemias while preserving privacy.

Nature · May 26, 2021Peer-reviewedBioinformatics