Determining the Set of Items to Include in Breast Operative Reports, Using Clustering Algorithms on Retrospective Data Extracted from Clinical DataWarehouse

Autor: Adrien Boukobza, Maxime Wack, Antoine Neuraz, Daniela Geromin, Cécile Badoual, Anne-Sophie Bats, Anita Burgun, Meriem Koual, Rosy Tsopra

Publikováno v: Advances in Informatics, Management and Technology in Healthcare
Advances in Informatics, Management and Technology in Healthcare, 295, IOS Press, pp.45-48, 2022, Studies in Health Technology and Informatics, ⟨10.3233/SHTI220656⟩

International audience; Medical reports are key elements to guarantee the quality, and continuity of care but their quality remains an issue. Standardization and structuration of reports can increase their quality, but are usually based on expert opi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::169e6bc7dd17364289a011ddb3d7b02f
https://pubmed.ncbi.nlm.nih.gov/35773802

Enriching UMLS-Based Phenotyping of Rare Diseases Using Deep-Learning: Evaluation on Jeune Syndrome

Autor: Carole Faviez, Marc Vincent, Nicolas Garcelon, Caroline Michot, Genevieve Baujat, Valerie Cormier-Daire, Sophie Saunier, Xiaoyi Chen, Anita Burgun

Publikováno v: Challenges of Trustable AI and Added-Value on Health
Challenges of Trustable AI and Added-Value on Health, 294, IOS Press; IOS Press, pp.844-848, 2022, Studies in Health Technology and Informatics, ⟨10.3233/SHTI220604⟩
Challenges of Trustable AI and Added-Value on Health, IOS Press, 2022, Studies in Health Technology and Informatics, ⟨10.3233/SHTI220604⟩

International audience; The wide adoption of Electronic Health Records (EHR) in hospitals provides unique opportunities for high throughput phenotyping of patients. The phenotype extraction from narrative reports can be performed by using either dict

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38fe78ee98700ba344966f7f0139a5ed
https://pubmed.ncbi.nlm.nih.gov/35612223

Modalités de mobilisation des cellules souches hématopoïétiques autologues et objectifs cellulaires en cellules CD34 + : recommandations de la Société francophone de greffe de mœlle et de thérapie cellulaire (SFGM-TC)

Autor: Fati Hamzy, Laure Vincent, Anne Brignier, Christine Giraud, Thi Ngoc Phuong Huynh, Francisca Nacimento, Aurélie Levavasseur, Virginie Ader, John De Vos, Katia Bellegarde, Marie-Agnès Guerout-Verite, Yves Rousseau, Ibrahim Yakoub-Agha

Publikováno v: Bulletin du Cancer
Bulletin du Cancer, 2020, 107 (1), pp.S44-S51. ⟨10.1016/j.bulcan.2019.08.007⟩

The modalities of mobilization of hematopoietic stem cells in autologous transplantation have evolved in recent years. The Francophone Society of Bone Marrow Transplantation and Cellular Therapy (SFGM-TC) organized the 9th hematopoietic stem cell tra

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::049f368d847e70041abcedcb03c92862
https://doi.org/10.1016/j.bulcan.2019.08.007

Model-based assessment of Chikungunya and O’nyong-nyong virus circulation in Mali in a serological cross-reactivity context

Autor: Hozé, Nathanaël, Diarra, Issa, Sangaré, Abdoul Karim, Pastorino, Boris, Pezzi, Laura, Kouriba, Bourèma, Sagara, Issaka, Dabo, Abdoulaye, Djimdé, Abdoulaye, Thera, Mahamadou Ali, Doumbo, Ogobara K., de Lamballerie, Xavier, Cauchemez, Simon

Publikováno v: Nature Communications
Nature Communications, 2021, 12 (1), pp.6735. ⟨10.1038/s41467-021-26707-9⟩
Nature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
Nature Communications, Nature Publishing Group, 2021, 12 (1), pp.6735. ⟨10.1038/s41467-021-26707-9⟩

Serological surveys are essential to quantify immunity in a population but serological cross-reactivity often impairs estimates of the seroprevalence. Here, we show that modeling helps addressing this key challenge by considering the important cross-

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::19c9a30602ee21dd96b2e50da3252d18
https://hal-pasteur.archives-ouvertes.fr/pasteur-03511907/file/s41467-021-26707-9.pdf

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium

Autor: Tsopra, Rosy, Fernandez, Xose, Luchinat, Claudio, Alberghina, Lilia, Lehrach, Hans, Vanoni, Marco, Dreher, Felix, Sezerman, O Ugur, Cuggia, Marc, de Tayrac, Marie, Miklasevics, Edvins, Itu, Lucian Mihai, Geanta, Marius, Ogilvie, Lesley, Godey, Florence, Boldisor, Cristian Nicolae, Campillo-Gimenez, Boris, Cioroboiu, Cosmina, Ciusdel, Costin Florian, Coman, Simona, Hijano Cubelos, Oliver, Itu, Alina, Lange, Bodo, Le Gallo, Matthieu, Lespagnol, Alexandra, Mauri, Giancarlo, Soykam, H Okan, Rance, Bastien, Turano, Paola, Tenori, Leonardo, Vignoli, Alessia, Wierling, Christoph, Benhabiles, Nora, Burgun, Anita, Sezerman, O.Ugur, Soykam, H.Okan

Publikováno v: BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making, 2021, 21 (1), pp.274. ⟨10.1186/s12911-021-01634-3⟩
BMC Medical Informatics and Decision Making, BioMed Central, 2021, 21 (1), pp.274. ⟨10.1186/s12911-021-01634-3⟩
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-14 (2021)

International audience; Abstract Background Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::f4a6da8cf5ab6041fe4d94cfca693431
https://www.hal.inserm.fr/inserm-03373629/file/s12911-021-01634-3.pdf