cadena adn
AI

Dx29: AI To Diagnose Rare Diseases

Dx29 is an Artificial Intelligence-assisted platform built to facilitate the analysis and diagnosis of rare diseases.

To help medical professionals make diagnoses artificial intelligence goes through four phases: phenotyping, genotyping, phenotype refinement and final evaluation. It first processes reports from different sources to extract symptoms and code them. Then it launches an automatic learning algorithm to classify the thousands of patient’s mutations according to their relationship with the phenotypes.

Then the AI suggests new symptoms for the physician to contrast and finally the system generates a classified list of possible pathologies with an assigned score.

CLIENT
Foundation29
Industry
Healthcare
Services
Artificial Intelligence
Technology
NPL
There are more than 6,000 pathologies that are difficult to diagnose and their treatment is a challenge for research.
This project is not motivated by profit but by the desire to collaborate in the research of rare diseases and contribute to our developments in Artificial Intelligence.
bebe medico estetoscopio
analisis investigacion laboratorio
01

Challenge

It is estimated that these diseases take, on average, about five years to be correctly diagnosed, and those who suffer from them have to see an average of eight specialists. And because they are less well known, one in four cases ends up being misdiagnosed.
sangre analisis test
laboratorio analisis cientifica
02

Results

This tool shows the percentage match between the symptoms and genetic data of the patient and those of other pathologies, so that the medical professional can rule out some diseases and focus on others.
“It will help to narrow down diagnoses when coping with difficult-to-diagnose illnesses``
gota analisis
03

Highlights

About one in four cases of rare diseases are misdiagnosed. As a result, 40 % of rare disease patients get worse.

Therefore, applying artificial intelligence in this field can help reduce all these figures and get better knowledge, accuracy, and diagnosis of this type of disease.

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