fda adverse event reports

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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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  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 ...

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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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  Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes

  • Published on: October, 2019
  • Carlos Soares, Luis Torgo, Vitor Cerqueira
  • Code Available

  Early detection of anomalous behavior of time series data is very important in many domains. The study deals with critical health event(CHE) that can ...

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  Predicting survival of patients with heart failure from serum creatinine and ejection fraction alone using machine learning

  • Published on: February, 2020
  • Giuseppe Jurman , Davide Chicco
  • Code Available

  Heart failure is a common event in Cardiovascular Diseases(CVD). Early detection and proper management can be a great help to people with CVD. Model s ...

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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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  CMS Medicare Fraud Detection

  • Published on: September, 2018
  • Tao Jin
  • Code Available

  Healthcare is a major industry in the U.S. with both private and government run programs. Healthcare fraud is a main problem that causes substantial m ...

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  Automated radiology report generation using conditioned transformers

  • Published on: March, 2021
  • Omar Alfarghaly and Rana Khaled and Abeer Elkorany and Maha Helal and Aly Fahmy
  • Code Available

  Automatically generate full radiology reports given chest X-ray images from the IU-X-Ray dataset by conditioning a recurrent neural net on the visual ...

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  Impact of Novel Aggregation Methods for Flexible Time-sensitive EHR Prediction Without Variable Selection or Cleaning

  • Published on: September, 2019
  • Jacob Deasy, Ari Ercole, Pietro Liò
  • Code Available

  The model includes improved aggregation methods for a flexible deep learning architecture which learns a joint representation of patient chart, lab an ...

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  Construction of Empirical Care Pathways Process Models from Multiple Real-World Datasets

  • Published on: February, 2020
  • Francisco Estupiñán-Romero, Juan González-García, Carlos Tellería-Orriols, Enrique Bernal-Delgado
  • Code Available

  The process models are a unique piece of information for health services research which are created using event logs and can help in visualizing start ...