Cargando…

A Process Mining Pipeline to Characterize COVID-19 Patients' Trajectories and Identify Relevant Temporal Phenotypes From EHR Data

The impact of the COVID-19 pandemic involved the disruption of the processes of care and the need for immediately effective re-organizational procedures. In the context of digital health, it is of paramount importance to determine how a specific patients' population reflects into the healthcare...

Descripción completa

Detalles Bibliográficos
Autores principales:	Dagliati, Arianna, Gatta, Roberto, Malovini, Alberto, Tibollo, Valentina, Sacchi, Lucia, Cascini, Fidelia, Chiovato, Luca, Bellazzi, Riccardo
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Public Health
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9168006/ https://www.ncbi.nlm.nih.gov/pubmed/35677768 http://dx.doi.org/10.3389/fpubh.2022.815674

Ejemplares similares

Health informatics and EHR to support clinical research in the COVID-19 pandemic: an overview
por: Dagliati, Arianna, et al.
Publicado: (2021)

An ICT infrastructure to integrate clinical and molecular data in oncology research
por: Segagni, Daniele, et al.
Publicado: (2012)

Using topological data analysis and pseudo time series to infer temporal phenotypes from electronic health records
por: Dagliati, Arianna, et al.
Publicado: (2020)

Patient-Generated Health Data Integration and Advanced Analytics for Diabetes Management: The AID-GM Platform
por: Salvi, Elisa, et al.
Publicado: (2019)

Integrated Multi-Omics Analyses in Oncology: A Review of Machine Learning Methods and Tools
por: Nicora, Giovanna, et al.
Publicado: (2020)

Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients
por: Keloth, Vipina K., et al.
Publicado: (2023)

Multi-Criteria Decision Making Approaches for Quality Control of Genome-Wide Association Studies
por: Malovini, Alberto, et al.
Publicado: (2009)

Multivariate Methods for Genetic Variants Selection and Risk Prediction in Cardiovascular Diseases
por: Malovini, Alberto, et al.
Publicado: (2016)

Hierarchical Naive Bayes for genetic association studies
por: Malovini, Alberto, et al.
Publicado: (2012)

Stochastic model search with binary outcomes for genome-wide association studies
por: Russu, Alberto, et al.
Publicado: (2012)

What do healthcare professionals need to turn risk models for type 2 diabetes into usable computerized clinical decision support systems? Lessons learned from the MOSAIC project
por: Fico, Giuseppe, et al.
Publicado: (2019)

Deep learning-based NLP data pipeline for EHR-scanned document information extraction
por: Hsu, Enshuo, et al.
Publicado: (2022)

Impact of COVID-19 lockdown on PM concentrations in an Italian Northern City: A year-by-year assessment
por: Pala, Daniele, et al.
Publicado: (2022)

Phenotype forecasting with SNPs data through gene-based Bayesian networks
por: Malovini, Alberto, et al.
Publicado: (2009)

Dataset on linear and non-linear indices for discriminating healthy and IUGR fetuses
por: Signorini, Maria G., et al.
Publicado: (2020)

Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data
por: Tang, Shengpu, et al.
Publicado: (2020)

Generalizable EHR-R-REDCap pipeline for a national multi-institutional rare tumor patient registry
por: Shalhout, Sophia Z, et al.
Publicado: (2022)

Leveraging process mining for modeling progression trajectories in amyotrophic lateral sclerosis
por: Tavazzi, Erica, et al.
Publicado: (2023)

EHR foundation models improve robustness in the presence of temporal distribution shift
por: Guo, Lin Lawrence, et al.
Publicado: (2023)

Linking glycemic dysregulation in diabetes to symptoms, comorbidities, and genetics through EHR data mining
por: Kirk, Isa Kristina, et al.
Publicado: (2019)

Effects of the Italian Law on Patient Safety and Health Professional Responsibilities Five Years after Its Approval by the Italian Parliament
por: Candido, Giuseppe, et al.
Publicado: (2023)

Modeling EHR with the openEHR approach: an exploratory study in China
por: Min, Lingtong, et al.
Publicado: (2018)

Inpatient EHR User Experience and Hospital EHR Safety Performance
por: Classen, David C., et al.
Publicado: (2023)

Physician Opinions about EHR Use by EHR Experience and by Whether the Practice had optimized its EHR Use
por: Jamoom, EW, et al.
Publicado: (2016)

Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing
por: Wulff, Antje, et al.
Publicado: (2020)

Reply to: Ethnic minorities, social media, and attitudes towards COVID-19 vaccination
por: Cascini, Fidelia, et al.
Publicado: (2022)

Modeling clinical activities based on multi-perspective declarative process mining with openEHR’s characteristic
por: Xu, Haifeng, et al.
Publicado: (2020)

A Novel Method to Enhance Pipeline Trajectory Determination Using Pipeline Junctions
por: Sahli, Hussein, et al.
Publicado: (2016)

A spatio-temporal mining approach towards summarizing and analyzing protein folding trajectories
por: Yang, Hui, et al.
Publicado: (2007)

The complex case of EHRs: examining the factors impacting the EHR user experience
por: Tutty, Michael A, et al.
Publicado: (2019)

Developing a Data-Driven Approach in Order to Improve the Safety and Quality of Patient Care
por: Cascini, Fidelia, et al.
Publicado: (2021)

Comparing the Certification Criteria for CCHIT-Certified Ambulatory EHR with the SNUBH's EHR Functionalities
por: Heo, Eun Young, et al.
Publicado: (2012)

Deep Learning to Unveil Correlations between Urban Landscape and Population Health †
por: Pala, Daniele, et al.
Publicado: (2020)

Ehre, wem Ehre gebührt: Prioritatenstreit um Entdeckung der direkten CP-Verletzung
Publicado: (1999)

TransformEHRs: a flexible methodology for building transparent ETL processes for EHR reuse
por: Pedrera-Jiménez, Miguel, et al.
Publicado: (2022)

ClustEHR: a tool for generating synthetic EHR data for unsupervised learning experiments.
por: Alexander, Nonie, et al.
Publicado: (2022)

THE PIPELINE OF GEROPSYCHOLOGY: INTEGRATION OF CLINICAL AND ACADEMIC CAREER TRAJECTORIES
por: Dorman, Hillary, et al.
Publicado: (2019)

EHR “SWAT” teams: a physician engagement initiative to improve Electronic Health Record (EHR) experiences and mitigate possible causes of EHR-related burnout
por: Sequeira, Lydia, et al.
Publicado: (2021)

How the Italian NHS Is Fighting Against the COVID-19 Emergency
por: Boccia, Stefania, et al.
Publicado: (2020)

Archetype-based conversion of EHR content models: pilot experience with a regional EHR system
por: Chen, Rong, et al.
Publicado: (2009)

Cannot write session to /tmp/vufind_sessions/sess_83cc19gg4lirabiu37qfduogff