This paper is in the following e-collection/theme issue:

Natural Language Processing (873) Advanced Data Analytics in eHealth (197) Big Data (305) Tools, Programs and Algorithms (362) Clinical Informatics (1265) Data Science (347) JMIR Theme Issue: COVID-19 Special Issue (2539) Public (e)Health, Digital Epidemiology and Public Health Informatics (957) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (81) AI Applications in Public Health (24)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54246, first published .
A New Natural Language Processing–Inspired Methodology (Detection, Initial Characterization, and Semantic Characterization) to Investigate Temporal Shifts (Drifts) in Health Care Data: Quantitative Study

A New Natural Language Processing–Inspired Methodology (Detection, Initial Characterization, and Semantic Characterization) to Investigate Temporal Shifts (Drifts) in Health Care Data: Quantitative Study

A New Natural Language Processing–Inspired Methodology (Detection, Initial Characterization, and Semantic Characterization) to Investigate Temporal Shifts (Drifts) in Health Care Data: Quantitative Study

Authors of this article:

Bruno Paiva1 Author Orcid Image ;   Marcos André Gonçalves1 Author Orcid Image ;   Leonardo Chaves Dutra da Rocha2 Author Orcid Image ;   Milena Soriano Marcolino3 Author Orcid Image ;   Fernanda Cristina Barbosa Lana3 Author Orcid Image ;   Maira Viana Rego Souza-Silva3 Author Orcid Image ;   Jussara M Almeida1 Author Orcid Image ;   Polianna Delfino Pereira3 Author Orcid Image ;   Claudio Moisés Valiense de Andrade1 Author Orcid Image ;   Angélica Gomides dos Reis Gomes4 Author Orcid Image ;   Maria Angélica Pires Ferreira5 Author Orcid Image ;   Frederico Bartolazzi6 Author Orcid Image ;   Manuela Furtado Sacioto7 Author Orcid Image ;   Ana Paula Boscato8 Author Orcid Image ;   Milton Henriques Guimarães-Júnior9 Author Orcid Image ;   Priscilla Pereira dos Reis10 Author Orcid Image ;   Felício Roberto Costa3 Author Orcid Image ;   Alzira de Oliveira Jorge11 Author Orcid Image ;   Laryssa Reis Coelho12 Author Orcid Image ;   Marcelo Carneiro13 Author Orcid Image ;   Thaís Lorenna Souza Sales1 Author Orcid Image ;   Silvia Ferreira Araújo14 Author Orcid Image ;   Daniel Vitório Silveira15 Author Orcid Image ;   Karen Brasil Ruschel1 Author Orcid Image ;   Fernanda Caldeira Veloso Santos16 Author Orcid Image ;   Evelin Paola de Almeida Cenci17 Author Orcid Image ;   Luanna Silva Monteiro Menezes1 Author Orcid Image ;   Fernando Anschau18 Author Orcid Image ;   Maria Aparecida Camargos Bicalho19 Author Orcid Image ;   Euler Roberto Fernandes Manenti20 Author Orcid Image ;   Renan Goulart Finger21 Author Orcid Image ;   Daniela Ponce22 Author Orcid Image ;   Filipe Carrilho de Aguiar23 Author Orcid Image ;   Luiza Margoto Marques7 Author Orcid Image ;   Luís César de Castro24 Author Orcid Image ;   Giovanna Grünewald Vietta25 Author Orcid Image ;   Mariana Frizzo de Godoy6 Author Orcid Image ;   Mariana do Nascimento Vilaça26 Author Orcid Image ;   Vivian Costa Morais7 Author Orcid Image
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Journals

  1. Coppolillo E, Mungari S, Ritacco E, Fabbri F, Minici M, Bonchi F, Manco G. Algorithmic Drift: A simulation framework to study the effects of recommender systems on user preferences. Information Processing & Management 2025;62(4):104125 View