Drug Discovery

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  Deep Reinforcement Learning for De Novo Drug Design

  • Published on: July, 2018
  • Olexandr Isayev, Mariya Popova, Alexander Tropsha
  • Code Available

  This model is an implementation of a novel computational strategy for de novo design of molecules with desired properties termed ReLeaSE (Reinforcemen ...

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  DeepSide - A Deep Learning Framework for Drug Side Effect Prediction

  • Published on: May, 2020
  • Oznur Tastan, A. Ercument Cicek, Halil Ibrahim Kuru
  • Code Available

  Drug failures due to unforeseen adverse effects at clinical trials pose health risks for the participants and lead to substantial financial losses. Si ...

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  Docking-based Virtual Screening with Multi-Task Learning

  • Published on: December, 2021
  • Hua Wu, Zijing Liu, Xianbin Ye, Haifeng Wang, Fan Wang, Xiaomin Fang
  • Code Available

  As the number of compounds in chemical libraries available to screening grows rapidly, machine learning approaches play an important role in docking-b ...

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  Named Entity Recognition-Detect Drug Information

  • Published on: March, 2021
  • John Snow Labs
  • Code Available

  It is a Pretrained NER deep learning model for posology (used for detecting drug Information) and is trained on the 2018 i2b2 dataset (no FDA) with em ...

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  Relation Extraction for Drug Information with NLP

  • Published on: September, 2020
  • John Snow Labs
  • Code Available

  It is a pretrained NER deep learning model for drug information relation extraction. The SparkNLP deep learning model (NerDL) is inspired by a former ...