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README.md

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+---
+tags:
+- chemistry
+- smiles
+- molecules
+- cheminformatics
+- classification
+pretty_name: COVID-19 Classification
+size_categories:
+- 1K<n<10K
+---
+
+# COVID-19 Classification
+
+Binary classification dataset of small molecules represented as SMILES for predicting anti‑coronavirus (SARS‑CoV‑2) activity.
+
+## Source
+- [Original dataset CSV](https://github.com/Harigua/ML_DD-applications/blob/main/COVID-19/data.csv)
+
+## Data fields
+- `smiles` (string): Canonical, isomeric SMILES. Unmodified from the source.
+- `label` (int): Binary activity label, {0: Inactive, 1: Active}.
+
+## Citation
+Harigua-Souiai, E.; Heinhane, M.M.; Abdelkrim, Y.Z.; Souiai, O.; Abdeljaoued-Tej, I.; Guizani, I. Deep Learning Algorithms Achieved Satisfactory Predictions When Trained on a Novel Collection of Anticoronavirus Molecules. Frontiers in Genetics, 2021, 12:744170. https://doi.org/10.3389/fgene.2021.744170
+
+Please cite the authors above if you use this dataset.

covid19-regression.parquet

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