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Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.

Journal of global health
BACKGROUND: Internet search engine data, such as Google Trends, was shown to be correlated with the incidence of COVID-19, but only in several countries. We aim to develop a model from a small number of countries to predict the epidemic alert level i...

Concept based auto-assignment of healthcare questions to domain experts in online Q&A communities.

International journal of medical informatics
BACKGROUND: Healthcare consumers are increasingly turning to the online health Q&A communities to seek answers for their questions because current general search engines are unable to digest complex health-related questions. Q&A communities are platf...

Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study.

JMIR public health and surveillance
BACKGROUND: The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries worldwide. Iran is one of the top 10 most affected countries. Search engines provide useful data from populations, and these data might be useful to ...

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...

Accurate spatiotemporal mapping of drug overdose deaths by machine learning of drug-related web-searches.

PloS one
Persons who inject drugs (PWID) are at increased risk for overdose death (ODD), infections with HIV, hepatitis B (HBV) and hepatitis C virus (HCV), and noninfectious health conditions. Spatiotemporal identification of PWID communities is essential fo...

Improving the accuracy of publicly available search engines in recognizing and classifying dental visual assets using convolutional neural networks.

International journal of computerized dentistry
AIM: To assess the accuracy of DigiBrain4, Inc (DB4) Dental Classifier and DB4 Smart Search Engine* in recognizing, categorizing, and classifying dental visual assets as compared with Google Search Engine, one of the largest publicly available search...

Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes.

Evolutionary computation
Selection hyper-heuristics (HHs) are randomised search methodologies which choose and execute heuristics during the optimisation process from a set of low-level heuristics. A machine learning mechanism is generally used to decide which low-level heur...

Unsupervised Phrase-Level Query Rewriting for Assisting Search in Clinical Free Text.

Studies in health technology and informatics
We report on the pilot evaluation of an experimental query-based search functionality that enables phrase-level query rewriting in an unsupervised way. It is intended for supporting search in clinical text. Qualitative evaluation is done by three cli...

Where to search top-K biomedical ontologies?

Briefings in bioinformatics
MOTIVATION: Searching for precise terms and terminological definitions in the biomedical data space is problematic, as researchers find overlapping, closely related and even equivalent concepts in a single or multiple ontologies. Search engines that ...