TY - JOUR
T1 - IMPatienT
T2 - An Integrated Web Application to Digitize, Process and Explore Multimodal PATIENt daTa
AU - Meyer, Corentin
AU - Romero, Norma Beatriz
AU - Evangelista, Teresinha
AU - Cadot, Brunot
AU - Laporte, Jocelyn
AU - Jeannin-Girardon, Anne
AU - Collet, Pierre
AU - Ayadi, Ali
AU - Chennen, Kirsley
AU - Poch, Olivier
N1 - Publisher Copyright:
© 2024-The authors.
PY - 2024/7/2
Y1 - 2024/7/2
N2 - Medical acts, such as imaging, lead to the production of various medical text reports that describe the relevant findings. This induces multimodality in patient data by combining image data with free-Text and consequently, multimodal data have become central to drive research and improve diagnoses. However, the exploitation of patient data is problematic as the ecosystem of analysis tools is fragmented according to the type of data (images, text, genetics), the task (processing, exploration) and domain of interest (clinical phenotype, histology). To address the challenges, we developed IMPatienT (Integrated digital Multimodal PATIENt daTa), a simple, flexible and open-source web application to digitize, process and explore multimodal patient data. IMPatienT has a modular architecture allowing to: (i) create a standard vocabulary for a domain, (ii) digitize and process free-Text data, (iii) annotate images and perform image segmentation, (iv) generate a visualization dashboard and provide diagnosis decision support. To demonstrate the advantages of IMPatienT, we present a use case on a corpus of 40 simulated muscle biopsy reports of congenital myopathy patients. As IMPatienT provides users with the ability to design their own vocabulary, it can be adapted to any research domain and can be used as a patient registry for exploratory data analysis. A demo instance of the application is available at https://impatient.lbgi.fr/.
AB - Medical acts, such as imaging, lead to the production of various medical text reports that describe the relevant findings. This induces multimodality in patient data by combining image data with free-Text and consequently, multimodal data have become central to drive research and improve diagnoses. However, the exploitation of patient data is problematic as the ecosystem of analysis tools is fragmented according to the type of data (images, text, genetics), the task (processing, exploration) and domain of interest (clinical phenotype, histology). To address the challenges, we developed IMPatienT (Integrated digital Multimodal PATIENt daTa), a simple, flexible and open-source web application to digitize, process and explore multimodal patient data. IMPatienT has a modular architecture allowing to: (i) create a standard vocabulary for a domain, (ii) digitize and process free-Text data, (iii) annotate images and perform image segmentation, (iv) generate a visualization dashboard and provide diagnosis decision support. To demonstrate the advantages of IMPatienT, we present a use case on a corpus of 40 simulated muscle biopsy reports of congenital myopathy patients. As IMPatienT provides users with the ability to design their own vocabulary, it can be adapted to any research domain and can be used as a patient registry for exploratory data analysis. A demo instance of the application is available at https://impatient.lbgi.fr/.
KW - artificial intelligence
KW - computer-Assisted
KW - computer-Assisted
KW - diagnosis
KW - electronic health records
KW - histology
KW - image processing
KW - Muscular diseases
UR - https://www.scopus.com/pages/publications/85198002157
U2 - 10.3233/JND-230085
DO - 10.3233/JND-230085
M3 - Article
C2 - 38701156
AN - SCOPUS:85198002157
SN - 2214-3599
VL - 11
SP - 855
EP - 870
JO - Journal of Neuromuscular Diseases
JF - Journal of Neuromuscular Diseases
IS - 4
ER -