AIMC Topic: Information Storage and Retrieval

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Automated information extraction from free-text medical documents for stroke key performance indicators: a pilot study.

Internal medicine journal
Automated information extraction might be able to assist with the collection of stroke key performance indicators (KPI). The feasibility of using natural language processing for classification-based KPI and datetime field extraction was assessed. Usi...

Technology Trends and Challenges for Large-Scale Scientific Visualization.

IEEE computer graphics and applications
Scientific visualization is a key approach to understanding the growing massive streams of data from scientific simulations and experiments. In this article, I review technology trends including the positive effects of Moore's law on science, the sig...

BioBERT and Similar Approaches for Relation Extraction.

Methods in molecular biology (Clifton, N.J.)
In biomedicine, facts about relations between entities (disease, gene, drug, etc.) are hidden in the large trove of 30 million scientific publications. The curated information is proven to play an important role in various applications such as drug r...

Optimal vocabulary selection approaches for privacy-preserving deep NLP model training for information extraction and cancer epidemiology.

Cancer biomarkers : section A of Disease markers
BACKGROUND: With the use of artificial intelligence and machine learning techniques for biomedical informatics, security and privacy concerns over the data and subject identities have also become an important issue and essential research topic. Witho...

Natural Language Processing-Assisted Literature Retrieval and Analysis for Combination Therapy in Cancer.

JCO clinical cancer informatics
PURPOSE: Despite advances in molecular therapeutics, few anticancer agents achieve durable responses. Rational combinations using two or more anticancer drugs have the potential to achieve a synergistic effect and overcome drug resistance, enhancing ...

MT-clinical BERT: scaling clinical information extraction with multitask learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Clinical notes contain an abundance of important, but not-readily accessible, information about patients. Systems that automatically extract this information rely on large amounts of training data of which there exists limited resources to...

Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: : Developing clinical natural language processing systems often requires access to many clinical documents, which are not widely available to the public due to privacy and security concerns. To address this challenge, we propose to develop...

Exploration of machine algorithms based on deep learning model and feature extraction.

Mathematical biosciences and engineering : MBE
The study expects to solve the problems of insufficient labeling, high input dimension, and inconsistent task input distribution in traditional lifelong machine learning. A new deep learning model is proposed by combining feature representation with ...

Privacy-protecting, reliable response data discovery using COVID-19 patient observations.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzing answers to COVID-19-related questions and posting these answers online.

A neuro-symbolic method for understanding free-text medical evidence.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We introduce Medical evidence Dependency (MD)-informed attention, a novel neuro-symbolic model for understanding free-text clinical trial publications with generalizability and interpretability.