Interoperability and similarity queries on medical databases

• Grant number: 20/11258-2
• Support type: Scholarships in Brazil - Post-Doctorate
• Effective date (Start): September 01, 2020
• Status: Discontinued
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal researcher: Marco Antonio Gutierrez
• Grantee: Mirela Teixeira Cazzolato
• Home Institution: Instituto do Coração Professor Euryclides de Jesus Zerbini (INCOR). Hospital das Clínicas da Faculdade de Medicina da USP (HCFMUSP). Secretaria da Saúde (São Paulo - Estado). São Paulo , SP, Brazil
• Associated research grant: 16/17078-0 - Mining, indexing and visualizing Big Data in clinical decision support systems (MIVisBD), AP.TEM
• Associated scholarship(s): 21/11403-5 - Mining multimodal records: explainable patterns and anomalies discovery, BE.EP.PD

Abstract

Health institutions store their patient data into their own repositories in their own repositories, using the structural particularities that each institution defines to carry out their activities. However, data for each individual are spread across many repositories in different institutions and formats, leading to frequent sharing of information between institutions. Given the differences in how and what data is recorded, there is a pressing need for standards for interoperability. One of the most recent and promising technologies for sharing medical data is based on the Common Model of Observational Data in Medicine (OMOP-CDM) proposed by OHDSI initiative. Data stored in EHR are fundamentally multimodal (images, videos, time series, etc.), acquired from distinct sources and with varying structures and formats that must be properly managed. This project aims at bridging both sources and formats, developing techniques to integrate results of previous GBdI research obtained with image-based medical examination data into OMOP. Although there is still no standardized support for similarity comparisons nor for complex data types such as images in OMOP, this research intends to provide it to MIVisDB Project and the area community. (AU)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CAZZOLATO, MIRELA T.; TRAINA, AGMA J. M.; BOHM, KLEMENS. Establishing trajectories of moving objects without identities: The intricacies of cell tracking and a solution. INFORMATION SYSTEMS, v. 105, MAR 2022. (20/11258-2, 16/17078-0, 20/07200-9, 18/24414-2)

GIUNTINI, FELIPE TALIAR; DE MORAES, KAUE L.; CAZZOLATO, MIRELA T.; KIRCHNER, LUZIANE DE FATIMA; DOS REIS, MARIA DE JESUS D.; TRAINA, AGMA J. M.; CAMPBELL, ANDREW T.; UEYAMA, JO. Modeling and Assessing the Temporal Behavior of Emotional and Depressive User Interactions on Social Networks. IEEE ACCESS, v. 9, p. 93182-93194, 2021. (13/07375-0, 20/11258-2, 18/24414-2, 18/17335-9, 16/17078-0, 20/07200-9)

GIUNTINI, FELIPE TALIAR; DE MORAES, KAUE L. P.; CAZZOLATO, MIRELA T.; KIRCHNER, LUZIANE DE FATIMA; DOS REIS, MARIA DE JESUS D.; TRAINA, AGMA J. M.; CAMPBELL, ANDREW T.; UEYAMA, JO. Tracing the Emotional Roadmap of Depressive Users on Social Media Through Sequential Pattern Mining. IEEE ACCESS, v. 9, p. 97621-97635, 2021. (18/24414-2, 20/07200-9, 13/07375-0, 16/17078-0, 20/11258-2, 18/17335-9)

CAZZOLATO, MIRELA T.; RAMOS, JONATHAN S.; RODRIGUES, LUCAS S.; SCABORA, LUCAS C.; CHINO, DANIEL Y. T.; JORGE, ANA E. S.; DE AZEVEDO-MARQUES, PAULO MAZZONCINI; JR, CAETANO TRAINA; TRAINA, AGMA J. M.. The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine. COMPUTERS IN BIOLOGY AND MEDICINE, v. 134, JUL 2021. (18/24414-2, 16/17078-0, 16/17330-1, 20/07200-9, 20/11258-2, 20/10902-5)