Optimisation des parcours patients pour lutter contre l'errance de diagnostic des patients atteints de maladies rares

10/27/2020
by   Frédéric Logé, et al.
0

A patient suffering from a rare disease in France has to wait an average of two years before being diagnosed. This medical wandering is highly detrimental both for the health system and for patients whose pathology may worsen. There exists an efficient network of Centres of Reference for Rare Diseases (CRMR), but patients are often referred to these structures too late. We are considering a probabilistic modelling of the patient pathway in order to create a simulator that will allow us to create an alert system that detects wandering patients and refers them to a CRMR while considering the potential additional costs associated with these decisions.

READ FULL TEXT
research
07/01/2019

Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks

Rare diseases affecting 350 million individuals are commonly associated ...
research
01/19/2017

Rare Disease Physician Targeting: A Factor Graph Approach

In rare disease physician targeting, a major challenge is how to identif...
research
07/03/2022

Patient-specific modelling, simulation and real time processing for respiratory diseases

Asthma is a common chronic disease of the respiratory system causing sig...
research
08/23/2022

POPDx: An Automated Framework for Patient Phenotyping across 392,246 Individuals in the UK Biobank Study

Objective For the UK Biobank standardized phenotype codes are associated...
research
03/13/2020

Tracing patients' PLOD with mobile phones: Mitigation of epidemic risks through patients' locational open data

In the cases when public health authorities confirm a patient with highl...
research
03/03/2018

A Conversational Interface to Improve Medication Adherence: Towards AI Support in Patient's Treatment

Medication adherence is of utmost importance for many chronic conditions...

Please sign up or login with your details

Forgot password? Click here to reset