AI Medical Compendium Topic:
Information Storage and Retrieval

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Applying citizen science to gene, drug and disease relationship extraction from biomedical abstracts.

Bioinformatics (Oxford, England)
MOTIVATION: Biomedical literature is growing at a rate that outpaces our ability to harness the knowledge contained therein. To mine valuable inferences from the large volume of literature, many researchers use information extraction algorithms to ha...

Consumer health information and question answering: helping consumers find answers to their health-related information needs.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Consumers increasingly turn to the internet in search of health-related information; and they want their questions answered with short and precise passages, rather than needing to analyze lists of relevant documents returned by search engi...

Using a simple open-source automated machine learning algorithm to forecast COVID-19 spread: A modelling study.

Advances in respiratory medicine
INTRODUCTION: Machine learning algorithms have been used to develop prediction models in various infectious and non-infectious settings including interpretation of images in predicting the outcome of diseases. We demonstrate the application of one su...

Bio-AnswerFinder: a system to find answers to questions from biomedical texts.

Database : the journal of biological databases and curation
The ever accelerating pace of biomedical research results in corresponding acceleration in the volume of biomedical literature created. Since new research builds upon existing knowledge, the rate of increase in the available knowledge encoded in biom...

Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We implement 2 different multitask learning (MTL) techniques, hard parameter sharing and cross-stitch, to train a word-level convolutional neural network (CNN) specifically designed for automatic extraction of cancer data from unstructured...

Extracting medications and associated adverse drug events using a natural language processing system combining knowledge base and deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Detecting adverse drug events (ADEs) and medications related information in clinical notes is important for both hospital medical care and medical research. We describe our clinical natural language processing (NLP) system to automatically...

2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This article summarizes the preparation, organization, evaluation, and results of Track 2 of the 2018 National NLP Clinical Challenges shared task. Track 2 focused on extraction of adverse drug events (ADEs) from clinical records and evalu...

Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a natural language processing system that identifies relations of medications with adverse drug events from clinical narratives. This project is part of the 2018 n2c2 challenge.

Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Identification of drugs, associated medication entities, and interactions among them are crucial to prevent unwanted effects of drug therapy, known as adverse drug events. This article describes our participation to the n2c2 shared-task in...