Anap announces the launch of a platform to share AI solutions deployed in nursing homes

At the beginning of last April, Anap (National Agency for Support to the Performance of Health and Medico-Social Establishments), announced the launch of a national platform to share artificial intelligence solutions deployed in health establishments. . It is possible to consult, for each of the referenced solutions, its history, its level of maturity, the number of users who benefit from it and the key success factors identified. The agency invites health establishments to come and share their AI projects.

Anap, a public expertise agency attached to the Ministry of Health, has the mission of meeting the needs of health and medico-social establishments through actions (methods, tools, events, interventions) developed with and for professionals.

Healthcare professionals use AI solutions (help with diagnosis and choice of treatments, forecasting patient flows or even automating tasks) to improve care, the patient experience and the internal organization of structures .

To support its deployment, Anap is launching a national platform for sharing AI solutions which makes it possible to reference projects carried out in healthcare establishments and to share key information on their design and deployment, in order to inspire all health actors.

Stéphane Pardoux, Managing Director of Anap says:

“This platform is a sharing space open to all professionals. Our objective: to give visibility to the artificial intelligence solutions deployed and to capitalize on these experiences! Artificial intelligence is a major performance lever for healthcare establishments: to provide better care, to streamline care and to save valuable time by automating certain administrative tasks. I call on professionals to take advantage of our platform, to share their solutions or
to come and find useful information for their projects. »

Raise awareness and facilitate access to best practices in AI

The website lists projects by category:

  • Organization,
  • data management,
  • predictive medicine,
  • Diagnostic,
  • patient follow-up,
  • Decision making,
  • Automation of tasks.

It will be regularly updated and professionals will be able to easily view the history and level of maturity of a project, the number of users who benefit from it and the key success factors identified.

Any professional can contact Anap to submit a project and be referenced. After the study of the project by a selection committee, the agency will be able to distribute the solution in question on its platform.

During the press release announcing the launch of this platform, Anap published the following focus on four solutions referenced on its platform:

SurgAR, Pr. Nicolas Bourdel, University Hospital of Clermont-Ferrand

The objective of the SurgAR project is to make it possible to display in augmented reality the internal structure of the organs during the surgical gesture carried out by a minimally invasive approach (use of a camera and small incisions). The organs thus become semi-transparent, the surgeon is truly guided in real time. This solution combining computer vision and artificial intelligence is intended to be deployed in operating theaters regardless of the laparoscopic surgery equipment they have.

An online version is also available for surgeons to practice using the tool. The entire project team is currently working on obtaining CE marking.

Professor Nicolas Bourdel explains:

“Beyond the development of initiatives combining fundamental and clinical research that can help health professionals, it is interesting to see to what extent these projects in the field of Artificial Intelligence must really also be exported as entities to full-fledged (startup / spinoff) outside the hospital and university environment in which they were born. There’s
There is therefore also an economic challenge, and more generally, a challenge in terms of how AI can create collaboration between hospitals, public research laboratories and private structures such as start-ups. »

SUOG: Dr. Ferdinand Dhombres, AP-HP

This project was born from the observation of a strong need for assistance in pregnancy ultrasound, linked in particular to the difficulties of access to experts and the complexity of the possible diagnoses.

The solution proposed by SUOG is based on mixed artificial intelligence, a combination of machine learning (for ultrasound image recognition) and symbolic reasoning algorithms based on ontologies. The source data comes from 10 expert centers in Europe for the most exhaustive coverage possible of the developmental anomalies listed by Orphanet, the portal for rare diseases.

The project’s prospects are now numerous. Large-scale clinical trials are planned from 2022, and the marketing of the project should see the light of day at the end of 2023.

Dr. Ferdinand Dhombres says:

“With 130,000 cases of birth defects and approximately 50,000 cases of ectopic pregnancy per year in Europe, the need for effective assistance with ultrasound screening has become critical. The SUOG assistant responds to the problem of access to sonographer experts and allows an improvement of ultrasounds for a better organization of perinatal care. »

Know Your Patient, GHICL

The project is hosted by the Group of Hospitals of the Catholic Institute of Lille (GHICL) and responds to a need to streamline the admission of patients and improve their journey within the establishments.

The solution is based in particular on the recovery of models of algorithms specific to the banking sector which automate the processing of identity documents, while providing a portal for admission officers. The perspectives specific to the project are based on the ongoing development of the third-party pathway (admission for a relative), the automatic recognition of the mutual card and the development of integration of the solution with other publishers of hospital information systems.

TransCUPtomics, Institut Curie

Faced with the difficulties of identifying the tissue origin of certain multi-metastatic cancers and when knowledge of the origin of a cancer generally serves as the basis for the implementation of an appropriate treatment, the Institut Curie has developed an artificial intelligence solution. Launched in 2019, this solution, now accessible to pathologists and oncologists, makes it possible to identify the tissue origin of cancers of unknown primary in order to be able to offer a targeted treatment to the patient. During the evaluation and validation phases, TransCUPtomics will have enabled the identification of 80% of cancerous tumours.

Discover all the projects referenced on

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Anap announces the launch of a platform to share AI solutions deployed in nursing homes

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