Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Enhancing Drug-Drug Interaction Extraction from Texts by Molecular Structure Information
Drug drug interaction extraction from the literature using a recursive neural network
A graph kernel based on context vectors for extracting drug-drug interactions
Extracting Drug-Drug Interactions with Attention CNNs
Application of Machine Learning in Knowledge Discovery for Pharmaceutical Drug-drug Interactions
ChemDataExtractor: A toolkit for automated extraction of chemical information from the scientific literature.
CHEMDNER: The drugs and chemical names extraction challenge
Ranking chemical structures for drug discovery: a new machine learning approach.
A novel integrated action crossing method for drug-drug interaction prediction in non-communicable diseases
GrEDeL: A Knowledge Graph Embedding Based Method for Drug Discovery From Biomedical Literatures
Label Propagation Prediction of Drug-Drug Interactions Based on Clinical Side Effects
PubChem as a public resource for drug discovery
PADME: A Deep Learning-based Framework for Drug-Target Interaction Prediction
similarity - based machine learning methods for predicting drug - target interactions : a brief review .
A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text
SPOT the Drug! An Unsupervised Pattern Matching Method to Extract Drug Names from Very Large Clinical Corpora
Data-Driven Prediction of Drug Effects and Interactions
Molecular Structure Extraction From Documents Using Deep Learning
Translational Biomedical Informatics and Pharmacometrics Approaches in the Drug Interactions Research
Extracting medication information from clinical text
Predicting undesirable drug interactions with promiscuous proteins in silico.
which type of motivation is capable of driving achievement behaviors such as exercise in different personalities ? by raja amjod .
Finding Structure in Time
Active Mobile Robot Localization
Learning to Segment via Cut-and-Paste
A General Retraining Framework for Scalable Adversarial Classification