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We are combining A.I. with medical science to help obstetricians to deal with weight gain of pregnant women.

Why weight control during pregnancy is a important?
A systematic review and meta-analysis of more than 1 million pregnant women, review that 47% had gestational weight gain greater than IOM recommendations and 23% had gestational weight gain less than IOM recommendations. And the research concludes that gestational weight gain greater than or less than guideline recommendations was associated with higher risk of adverse maternal and infant outcomes.
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Learn more
Routine Checkup
We are building  an innovation to give obstetricians the advantage to know if pregnant woman is following  guideline recommendations of gestational weight gain .
Percentage of American women below, within, and above pregnancy weight gain recommendations
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Epidemiology of gestational diabetes mellitus according to IADPSG/WHO 2013 criteria among obese pregnant women in Europe

The prevalence of gestational diabetes mellitus (GDM) diagnosed by the IADPSG/WHO 2013 GDM criteria in European pregnant women with a BMI ≥29.0 kg/m2 is substantial, and poses a significant health burden to these pregnancies and to the future health of the mother and her offspring. Uniform criteria for GDM diagnosis, supported by robust evidence for the benefits of treatment, are urgently needed to guide modern GDM screening and treatment strategies.

Predictors of excess birth weight in Brazil: a systematic review

The main predictors for excess birth weight in Brazil are modifiable risk factors. The implementation of adequate nutritional status in the gestational period and even after childbirth appears to be due to the quality and frequency of the follow-up of the mothers and their children by public health agencies.

Medical Consultation


It is easy! For this phase of our project we are looking for a very simple support. What  we need  is to:
1) Talk about our idea. We want to learn about ethics, features, and a possible impact in the medical practice.
2) Get anonymous data of pregnant woman to understand the behavior of weight fluctuation.
3) Discuss possible outcomes of our findings.
4) Participate, whether the results encourage us, to continue our research.

What we are developing?

Today, we have an algorithm that uses A.I. to learn the natural weight fluctuation of an individual to forecast, two weeks in the future, the weight range trend of our users (

With pregnant woman, we want to define an initial weight gain curve and then monitor weight whether this woman is following this initial normal curve and anticipate, in two to three weeks if that person is going to gain, maintain our losing weight.
Our objective is to collaborate with medical doctors to reduce pregnancy risks.
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Our team


Renato Romani MD MBA

Medical doctor

Medical doctor with specialization in sports medicine and medical informatics. MBA at the University of Minnesota and entrepreneur training  at the University of Wisconsin. Assistant prof. at Sao Paulo Federal University in Sports Medicine and Exercise Physiology.  

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Bobby Bahov


Serial entrepreneur with passion for exponential technologies and their effects on everyday life and business.

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Ahmed Rbaibi

Chief Data Scientist AI Lab

A data scientist with passion for innovation and business development.


Hall of fame of collaborators

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Be the first to collaborate :)

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How to collaborate?

It is very simple and easy!

We don't want to create work or any kind of problems to our collaborators. In this phase of our research we just need just talk and understand the feasibility of our project.

So, could be a 15 min call :)

But of course, we would love to get data, which is a series of weight from pregnant woman, and this will be anonymous and we will sign a document to be sure that every point of privacy and ethics is reached.

Please fill this form up and I will replay to you with more details.

I hope to receive your message soon!

Best regards,

Renato Romani MD MBA

Start with your questions

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Other sources of information

Weight Gain During Pregnancy: Reexamining the Guidelines

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