Clinical Trials

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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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  A Bayesian time-to-event pharmacokinetic model for phase I dose-escalation trials with multiple schedules

  • Published on: July, 2019
  • S Weber, BK Günhan, and T Friede
  • Code Available

  TITE-PK (a time-to-event pharmacokinetic model) is a method for designing and analyzing phase I dose-escalation trials with multiple schedules, eg a d ...

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  GAMENet - Graph Augmented Memory Networks for Recommending Medication Combination

  • Published on: November, 2018
  • Hongyan Li, Tengfei Ma, Jimeng Sun, Cao Xiao, Junyuan Shang
  • Code Available

  When it comes to recommend medication combination for patients with complex health conditions, existing deep learning approaches either do not customi ...

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  Adverse Drug Reaction(ADR)-Target Association Prediction

  • Published on: July, 2020
  • Bumjun Kim, Seda Arat, Robert Ietswaart, William DuMouchel, Saman Farahmand, Amanda X. Chen
  • Code Available

  Adverse reactions of marketed and approved drugs cause a significant amount of morbidity and mortality. To associate these drugs with human adverse dr ...

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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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  Detect adverse drug events in clinical text, tweets and reviews

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

   It is a pretrained NER deep learning model used for detecting adverse reactions of drugs in reviews, tweets, and medical text, and is compatible with ...

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  Comparative Effectiveness Research

  • Published on: January, 2017
  • CitiusTech

  A machine learning model is developed to assist decision-makers in determining real-world performance of their novel drug against key hard end-points ...

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  Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data

  • Published on: May, 2018
  • Peggy Peissig, Richard Maclin and David Page, Zhaobin Kuang, Vítor Santos Costa
  • Code Available

  Adverse drug events can lead to health hazards and have raised awareness of industries and governments internationally about pharmacovigilance. Baseli ...