AIMC Topic: Knowledge Discovery
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Explaining deep neural networks for knowledge discovery in electrocardiogram analysis.
Scientific reports
May 26, 2021
Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any deep learning-based prediction...
Examining the concept of equity in community psychology with natural language processing.
Journal of community psychology
May 18, 2021
Large amounts of text-based data, like study abstracts, often go unanalyzed because the task is laborious. Natural language processing (NLP) uses computer-based algorithms not traditionally implemented in community psychology to effectively and effic...
Artificial Intelligence in Action: Addressing the COVID-19 Pandemic with Natural Language Processing.
Annual review of biomedical data science
May 14, 2021
The COVID-19 (coronavirus disease 2019) pandemic has had a significant impact on society, both because of the serious health effects of COVID-19 and because of public health measures implemented to slow its spread. Many of these difficulties are fund...
Neural networks for open and closed Literature-based Discovery.
PloS one
May 15, 2020
Literature-based Discovery (LBD) aims to discover new knowledge automatically from large collections of literature. Scientific literature is growing at an exponential rate, making it difficult for researchers to stay current in their discipline and e...
Recognizing software names in biomedical literature using machine learning.
Health informatics journal
Sep 30, 2019
Software tools now are essential to research and applications in the biomedical domain. However, existing software repositories are mainly built using manual curation, which is time-consuming and unscalable. This study took the initiative to manually...
A Precision Environment-Wide Association Study of Hypertension via Supervised Cadre Models.
IEEE journal of biomedical and health informatics
May 20, 2019
We consider the problem in precision health of grouping people into subpopulations based on their degree of vulnerability to a risk factor. These subpopulations cannot be discovered with traditional clustering techniques because their quality is eval...
A survey on literature based discovery approaches in biomedical domain.
Journal of biomedical informatics
Mar 9, 2019
Literature Based Discovery (LBD) refers to the problem of inferring new and interesting knowledge by logically connecting independent fragments of information units through explicit or implicit means. This area of research, which incorporates techniq...
Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD.
BMC medical informatics and decision making
Jan 31, 2019
BACKGROUND: Disease comorbidity is very common and has significant impact on disease treatment. Revealing the associations among diseases may help to understand the mechanisms of diseases, improve the prevention and treatment of diseases, and support...
Incorporating Knowledge-Driven Insights into a Collaborative Filtering Model to Facilitate the Differential Diagnosis of Rare Diseases.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Rare diseases, although individually rare, collectively affect one in ten Americans. Because of their rarity, patients with rare diseases are typically left misdiagnosed or undiagnosed, which leads to a prolonged medical journey. The diagnosis pathwa...
Exploring Active Learning Based on Representativeness and Uncertainty for Biomedical Data Classification.
IEEE journal of biomedical and health informatics
Nov 13, 2018
Nowadays, there is an abundance of biomedical data, such as images and genetic sequences, among others. However, there is a lack of annotation to such volume of data, due to the high costs involved to perform this task. Thus, it is mandatory to devel...
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