AIMC Topic: Epidemiological Monitoring
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Forecasting influenza-like illness dynamics for military populations using neural networks and social media.
PloS one
Dec 15, 2017
This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of histo...
The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance.
Applied clinical informatics
May 31, 2017
OBJECTIVES: This study evaluates the accuracy and portability of a natural language processing (NLP) tool for extracting clinical findings of influenza from clinical notes across two large healthcare systems. Effectiveness is evaluated on how well NL...
The early bird catches the term: combining twitter and news data for event detection and situational awareness.
Journal of biomedical semantics
Oct 7, 2016
BACKGROUND: Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. They can therefore be highly useful for event detection and si...
Automatic classification of diseases from free-text death certificates for real-time surveillance.
BMC medical informatics and decision making
Jul 15, 2015
BACKGROUND: Death certificates provide an invaluable source for mortality statistics which can be used for surveillance and early warnings of increases in disease activity and to support the development and monitoring of prevention or response strate...
Fuzzy association rule mining and classification for the prediction of malaria in South Korea.
BMC medical informatics and decision making
Jun 18, 2015
BACKGROUND: Malaria is the world's most prevalent vector-borne disease. Accurate prediction of malaria outbreaks may lead to public health interventions that mitigate disease morbidity and mortality.
Global Epidemiology of Outbreaks of Unknown Cause Identified by Open-Source Intelligence, 2020-2022.
Emerging infectious diseases
Feb 1, 2025
Epidemic surveillance using traditional approaches is dependent on case ascertainment and is delayed. Open-source intelligence (OSINT)-based syndromic surveillance can overcome limitations of delayed surveillance and poor case ascertainment, providin...
Use of artificial intelligence for health care-associated infection surveillance: Correspondence.
American journal of infection control
Jul 1, 2024
Response to the letter to the editor regarding "Assisting the Infection Preventionist: Use of Artificial Intelligence for Healthcare-Associated Infection Surveillance".
American journal of infection control
Jul 1, 2024
Artificial intelligence and TB management - The way forward.
The Indian journal of tuberculosis
Jan 1, 2020
Predictive analysis across spatial scales links zoonotic malaria to deforestation.
Proceedings. Biological sciences
Jan 16, 2019
The complex transmission ecologies of vector-borne and zoonotic diseases pose challenges to their control, especially in changing landscapes. Human incidence of zoonotic malaria ( Plasmodium knowlesi) is associated with deforestation although mechani...
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