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Drug Induced Autoimmunity Prediction

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About

This dataset comprises molecular descriptors generated using RDKit, specifically curated for the study of drug-induced autoimmunity through ensemble machine learning approaches. It is divided into a training set and a testing set, containing numerical features that represent molecular properties and structural characteristics of drugs. The dataset supports predictive modeling tasks aimed at identifying potential autoimmune risks associated with drug candidates. These molecular descriptors include physicochemical properties, providing a comprehensive foundation for machine learning analysis. The dataset facilitates the development of interpretable models for drug toxicity prediction, contributing to advancements in computational toxicology and drug safety assessment.
Subject Area
Health and Medicine
Instances
477
Features
195
Data Types
Tabular
Tasks
Classification
Feature Types
Categorical

Features

NameRoleTypeUnitsMissing Values

Additional Metadata

Authors
Xiaojie Huang
Year Created
2025
License
CC BY 4.0