Our explorations
Kaduceo continues to explore and invest in research to develop our expertise in health data and exploit its full potential.
Essential values in Kaduceo’s corporate project, research and exploration are fully integrated in our daily life and our projects.
European research project: H2020 REMEDIA
Kaduceo is a member of the European consortium engaged to study the impact of environmental exposure on respiratory diseases.
Trajectory and care pathway
Patient clustering - Process mining - Data visualization
Complex and valuable data
To meet the quality requirements of the French health care system, it is necessary to place the patient at the center of the analyses and to have a good knowledge of their care pathways. The French National Health Data System (SNDS) is a valuable source of information for studying care pathways. These data are complex and include many categories of care: hospitalizations, consultations, medical and biological procedures, treatments and medical devices...
Our research aims to make these data interpretable and to develop robust and efficient tools for the classification, modeling and visualization of care trajectories.
Patient profiling
The identification of groups of patients with similar management, of typical pathway "profiles", and of a synthetic representation of these pathways, offers the possibility of questioning the efficiency of management. And this makes it possible to designate the most appropriate pathways from a medical and economic point of view.
Modeling and prediction of emergency room flows
Time series - Deep learning - Memory models
Observations and issues
The current situation in emergency departments is particularly difficult. Their overcrowding compromises the quality of care, and the exhausted nursing staff is faced with a feeling of helplessness. The peaks of affluence are particularly pronounced during epidemic periods, whether seasonal (bronchilitis, influenza, grastro-enteritis) or occasional (covid-19). More generally, the aging of the population, the difficulty of access to a city doctor, unjustified visits, etc. only aggravate the situation.
Development of our own models
We develop AI models (RNN) to predict patient flows, their impact on the different services, and to anticipate peaks in activity in the event of an epidemic. A better visibility on the expected level of affluence gives the hospital the possibility to react earlier and avoid saturation of its services.
Explicability of models and prediction results
Project carried out in collaboration with the Institut de Recherche en Informatique de Toulouse
Medical Imaging - Ophthalmology
Classification - Segmentation - Interpretability
Artificial intelligence and the future
Artificial intelligence technologies for medical image analysis promise great progress in facilitating the diagnosis of diseases and the interpretation of images. And they are all the more relevant in ophthalmology, where imaging plays a major role.
We are currently working on AI models for retinal disease screening and automatic anomaly detection.
Supporting practitioners
The objective is to allow ophthalmologists to save time or to delegate the diagnostic task. We also propose a tool for image annotation that allows us to collect reliable data, interpreted by experts, and all the more appropriate for the training of our models.
An idea ? A project ?
Kaduceo USA
725 Cool Springs Bld, FRANKLIN, TN, 37067
Kaduceo France
31 Allée Jules Guesde, 31400 Toulouse, France