Title :

ClinMine: Optimizing the Management of Patients in Hospital

Author(s) :

Dhaenens, Clarisse [Auteur]
Operational Research, Knowledge And Data [ORKAD]
Jacques, Julie [Auteur]
Université catholique de Lille [UCL]
Vandewalle, Vincent [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Université de Lille
Vandromme, Maxence [Auteur]
Operational Research, Knowledge And Data [ORKAD]
Chazard, Emmanuel [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Preda, Cristian [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Université de Lille
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Amarioarei, Alexandru [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Chaiwuttisak, Porpimol [Auteur]
Operational Research, Knowledge And Data [ORKAD]
Cozma, Cristina [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Ficheur, Grégoire [Auteur]
Université de Lille
Kessaci, Marie-Éléonore [Auteur]
Operational Research, Knowledge And Data [ORKAD]
Perichon, Renaud [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Taillard, Julien [Auteur]
Alicante [Seclin]
Bordet, Régis [Auteur]
Département de Pharmacologie Médicale [Lille] [Pôle Recherche]
Faculté de Médecine Henri Warembourg - Université de Lille
Lansiaux, Apolline [Auteur]
Génétique moléculaire et approches thérapeutiques des hémopathies malignes
Jourdan, Laetitia [Auteur]
Operational Research, Knowledge And Data [ORKAD]
Delerue, David [Auteur]
Alicante [Seclin]
Hansske, Arnaud [Auteur]
Groupe Hospitalier de l'Institut Catholique de Lille [GHICL]

Journal title :

Innovation and Research in BioMedical engineering

Pages :

83-92

Publisher :

Elsevier Masson

Publication date :

2018-01

ISSN :

1959-0318

English keyword(s) :

electronic health records.
statistical analysis
optimization algorithms
heterogeneous data
patient pathway
Hospital information system
temporal data

HAL domain(s) :

Sciences du Vivant [q-bio]/Médecine humaine et pathologie
Statistiques [stat]
Informatique [cs]
Sciences du Vivant [q-bio]/Santé publique et épidémiologie

English abstract : [en]

A better understanding of “patient pathway” thanks to data analysis can lead to better treatments for patients. The ClinMine project, supported by the The French National Research Agency (ANR), aims at proposing, from ...
Show more >A better understanding of “patient pathway” thanks to data analysis can lead to better treatments for patients. The ClinMine project, supported by the The French National Research Agency (ANR), aims at proposing, from various case studies, algorithmic and statistical models able to handle this type of pathway data, focusing primarily on hospital data. This article presents two of these case studies, focusing on the integration of temporal data within analysis. First, the hypothesis that some aspects of the patient pathway can be described, even predicted, from the management process of the hospital medical mail is studied. Therefore a specific functional data analysis is driven, and several types of patients have been detected. The second case study deals with the detection of profiles through a biclustering of the patients. The difficulty to simultaneously deal with heterogeneous data, including temporal data is exposed and a method is proposed. Results on real data show the effectiveness of the proposed method.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Optimisation de la prise en Charge des Patients à l'Hôpital

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL