An extensive survey on the use of supervised machine learning techniques in the past two decades for prediction of drug side effects
P Das, DH Mazumder - Artificial Intelligence Review, 2023 - Springer
Approved drugs for sale must be effective and safe, implying that the drug's advantages
outweigh its known harmful side effects. Side effects (SE) of drugs are one of the common …
outweigh its known harmful side effects. Side effects (SE) of drugs are one of the common …
Predicting neurological adverse drug reactions based on biological, chemical and phenotypic properties of drugs using machine learning models
S Jamal, S Goyal, A Shanker, A Grover - Scientific reports, 2017 - nature.com
Adverse drug reactions (ADRs) have become one of the primary reasons for the failure of
drugs and a leading cause of deaths. Owing to the severe effects of ADRs, there is an urgent …
drugs and a leading cause of deaths. Owing to the severe effects of ADRs, there is an urgent …
Lo-hi: Practical ml drug discovery benchmark
S Steshin - Advances in Neural Information Processing …, 2023 - proceedings.neurips.cc
Finding new drugs is getting harder and harder. One of the hopes of drug discovery is to use
machine learning models to predict molecular properties. That is why models for molecular …
machine learning models to predict molecular properties. That is why models for molecular …
Machine learning-based methods and novel data models to predict adverse drug reaction
Predicting adverse drug reactions (ADRs) plays a critical role in developing new drugs and
preventing adverse reactions during the treatment of existing drugs. However, with the rapid …
preventing adverse reactions during the treatment of existing drugs. However, with the rapid …
MLCNNF: A Multi-Label Convolutional Neural Network Framework for Predicting Adverse COVID Drug Reactions From the Chemical Structure
P Das, DH Mazumder - IEEE Transactions on Computational …, 2025 - ieeexplore.ieee.org
COVID-19 is a novel disease that currently has relatively few drugs available for treatment.
Adverse COVID Drug Reactions (ACDR) are a major concern in the drug development …
Adverse COVID Drug Reactions (ACDR) are a major concern in the drug development …
K1K2NN: A novel multi-label classification approach based on neighbors for predicting COVID-19 drug side effects
P Das, DH Mazumder - Computational Biology and Chemistry, 2024 - Elsevier
Abstract COVID-19, a novel ailment, has received comparatively fewer drugs for its
treatment. Side Effects (SE) of a COVID-19 drug could cause long-term health issues …
treatment. Side Effects (SE) of a COVID-19 drug could cause long-term health issues …
A hierarchical anatomical classification schema for prediction of phenotypic side effects
Prediction of adverse drug reactions is an important problem in drug discovery endeavors
which can be addressed with data-driven strategies. SIDER is one of the most reliable and …
which can be addressed with data-driven strategies. SIDER is one of the most reliable and …
Comprehensive assessment of Indian variations in the druggable kinome landscape highlights distinct insights at the sequence, structure and pharmacogenomic …
India confines more than 17% of the world's population and has a diverse genetic makeup
with several clinically relevant rare mutations belonging to many sub-group which are …
with several clinically relevant rare mutations belonging to many sub-group which are …
[HTML][HTML] K1K2NN: A Novel Multi-Label Classification Approach Based on Neighbours to Predict Covid Drug Side Effects from Chemical Properties
DH Mazumder, P Das - 2023 - europepmc.org
Abstract COVID-19, a novel ailment, has received comparatively fewer drugs for its
treatment. Side Effects (SE) of a covid drug could cause long-term health issues. Hence, SE …
treatment. Side Effects (SE) of a covid drug could cause long-term health issues. Hence, SE …
[PDF][PDF] A Data and Informatics Driven Drug Discovery Framework to Bridge Traditional and Modern Medicine
S Pande, G Bagler - Advanced Techniques in Biology and Medicine, 2015 - academia.edu
Abstract Systems biological models of complex diseases provide a rational way to target
their molecular control mechanisms. On the other hand, traditional medicinal systems offer …
their molecular control mechanisms. On the other hand, traditional medicinal systems offer …