Author

Mallika Sanyal

St Xavier’s CollegeORCID 0000-0001-9113-8846Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Approach:machine learning (classical)· 2 Assay:electronic health records· 1 Organism:human· 1

Frequent Co-Authors

Daxesh P. PateliD· 2 shared Pranav S. ShrivastaviD· 2 shared Tanviben PateliD· 2 shared Hoda El-Sayed· 1 shared

Activity by Year

2023-2024 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Daxesh P. PatelORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 11, 2024

Comparative assessment of machine learning algorithms to predict severity of disease in COVID-19 patients based on eight cofactors

Tanviben Patel, Daxesh P. Patel, Hoda El-Sayed…·Pranav S. Shrivastav

The paper compares machine learning algorithms to predict COVID-19 severity using eight cofactors and finds that most algorithms outperform SVM based on AUC scores.

DOI 10.1101/2024.10.11.617884

humanelectronic health records

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BioinformaticsbioRxivPreprintJun 9, 2023

Prediction of Heart Disease and Survivability using Support Vector Machine and Naive Bayes Algorithm

Tanviben Patel, Daxesh P. Patel, Mallika Sanyal, Pranav S. Shrivastav

This paper compares SVM and Naive Bayes algorithms for predicting heart disease and survivability using a clinical dataset, finding Naive Bayes achieves 93% accuracy for survivability.

9 citations

machine learning (classical)differential expression

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