PROUD TO ANNOUNCE THAT
Mission
DEEPECHO IS AN AI PRODUCT DEVELOPED BY DOCTORS AND AI SCIENTISTS & AIMING AT REINFORCING ANTENATAL DIAGNOSIS
450 newborn children
die every single hour…
Mainly from preventable causes.
We are on a mission to reduce infant and maternal mortality rate caused by ultrasound diagnosis mistakes.
We are working on building a solution tackling the Millennium Development Goal 4 on reducing child mortality rates.
450 newborn children die every hour, mainly from preventable causes, which is unconscionable in the 21st century.
PRODUCT
Une offre exclusive pour des résultats data en trois semaines, activables aussitôt.
Through high-performance Deep Learning algorithms we are working on a software to prevent birth defects, address preterm birth, low birth weight, and their outcomes.
We are getting a computer to mimic what a trained sonographer would do and simplify ultrasound so that minimally trained clinical professionals assisted by AI technologies, can also use it in nontraditional healthcare settings.
Original image
taken by the sonographer
Abdominal standard
plane detection
VALUE PROPOSITION
ACCURATE ANTENATAL ULTRASOUND DIAGNOSIS ANYWHERE & IN NO TIME
A decision-making support system
Train advanced Deep Learning Algorithms to real-time identify and help the practitioner to detect and locate standard plans during prenatal ultrasoun diagnosis & automatically take accurate measurements.
A decision-making support system
Set up an automatic system to calculate biometric measurements through a segmentation of the anatomical landmarks and help the practitioner come up with the right medical diagnosis.
A remote ultrasound software
Develop a decision support software to help tomorrow with teleguidance and remote diagnosis. We are looking to democratize access to quality ultrasound diagnosis for prenatal care.
RESULTS
WHAT WE HAVE ACCOMPLISHED SO FAR
98
CLASIFICATION ACCURACY
Our deep neural models are able to recognize standard views and detect key standard planes including the transthalamic, abdominal and femoral views with very high accuracy.
95
SEGMENTATION ACCURACY
We have build Algorithms able to measure the main fetal structures with extreme precision, based on one of the world’s biggest annotated fetal ultrasound image database.
15
FGR DIAGNOSIS
DeepEcho is able to diagnose Fetal Growth Restriction (one of the leading causes of neonatal deaths and birth defects) and we are currently working on in vivo clinical trials to publish our results in the coming months.
ACHIEVEMENTS
WE MAKE MEDICAL & AI EXPERTS TALK TOGHETER
World class curated dataset
One of the world’s biggest dataset (*) for fetal ultrasound images, with best in class medical input, annotated by some of excellent experts in the field and constantly fed by our medical partners.
Health center partnerships
More than 5 health center partnerships – and counting – to fuel our algorithms with Data, to share with us their expertise and needs, and to deploy our solution on the field.
Medical validation
Our work and strategy is driven by our medical roadmap, we will be in the coming months releasing what is probably worldwide one of the first clinical studies on the uses of AI in ultrasound diagnosis for prenatal care
(*) : Burgos-Artizzu, X.P., Coronado-Gutiérrez, D., Valenzuela-Alcaraz, B. et al. Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes. Sci Rep 10, 10200 (2020).
PARTNERS
PROUDLY TRUSTED & SUPPORTED BY
MICROSOFT FOR STARTUPS
Advanced startups batch
NVIDIA
Inception Program
PLUG AND PLAY
Venture Capital
UM6P VENTURES
Venture Capital
AI R&D LABS
DEEPECHO’S SCIENTIFIC ECOSYSTEM
Laboratory of Computer Science, Artificial Intelligence and Pattern Recognition, Mohammed V University in Rabat, Morocco
Research Laboratory of Telecommunications Systems, Networks and Services INPT Rabat, Morocco
Research Laboratory in Information Systems, Intelligent Systems and Mathematical Modelling
Rabat, Morocco
DEEPECHO TEAM
WHO WE ARE
Professor/Researcher in Machine Learning,
Mohammed V University in Rabat.
+10 years of ML experience.
Mohammed V University in Rabat.
+10 years of ML experience.
Chief Science Officer,
PhD, 30 years of AI research, focus on R&D
PhD, 30 years of AI research, focus on R&D
Ecole Centrale, Paris
ESSEC Grande Ecole, Paris
Ex JP Morgan & Macquarie London
ESSEC Grande Ecole, Paris
Ex JP Morgan & Macquarie London
PhD in AI, INPT
Focus on Deep Learning
Deepecho model Architecture
Focus on Deep Learning
Deepecho model Architecture
Doctor in Radiology Casablanca University Hospital,
Passionate about the potential of AI in Medicine and radiology
Passionate about the potential of AI in Medicine and radiology
PhD in NLP, FSR
Focus on NLP for clinical reports
Focus on NLP for clinical reports