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Alexej William Arthur commented on Evidence-based Parenthood Companion

Hi Kate,
Thanks for having us.

Your Question: Would you be able to tell me more about how the solution will be personalized?

Once a person gets confronted with great news of their forthcoming parenthood, they find themselves in a very unique situation with interindividual variability. This is determined by their precise location, their environment, their resources and most importantly access to professional advice and support. Our solution will take all these factors into account by:

- reference to geographical data to determine the medical support network (comprised of midwife, pediatrician, psychologist, obstetrician, nutritionist, etc.) most optimal to the specific needs of the becoming parent
- acquisition of expert-curated content related to the exact stage and particular features of the infant’s development (common symptoms, mandatory regular checkups, etc.), which can be voluntarily provided by each parent (see next section)
- increasingly tailoring actionable recommendations, based on past interactions with the app, to prevent and resolve complications during pregnancy, as well as malignancies during early childhood

In contrast to many solutions purely based on deep learning technology, we do not want to rely on it to solve the entire problem. However, we want to leverage its strengths to more effectively foster the interpersonal relationships that gain importance in care now more than ever.

Your Question: What information would the parents submit?

At registration, parents would need to submit only a minimal set of information to allow the app a general characterization of the aforementioned individual context. We envisage that at least the following inputs will be required: name, age, (prospective) date of child’s birth and location.

Once our timeline feature is generated, the becoming parent will occasionally be involved to contribute additional context. This will serve as a means for his medical support network to identify potential risks for mother and child. We are aware that this is a very personal interaction, so all communication to experts will be secured through modern encryption.

Your Question: How will you use big data?

Beyond the MVP, this kind of survey of additional context from each user may act as a source for a learning algorithm, where anonymously provided information can be correlated along the timeline to achieve higher prediction accuracy and thus, more efficient care and support in the future.

Moreover, we may consider involving third party products such as GoogleHealth, CardioSecur, etc., to compile a more complete picture of the individual medical state of parent and child and provide even more personalized, actionable recommendations.

Your Question: What are the next steps to developing your idea?

We are currently developing the idea and testing conceptual early-stage prototypes. As a next step, we want to build a small-scale prototype and test it with midwives and expecting parents in Berlin (Germany) to gather feedback. Another step will be to launch a website/blog showcasing our ideas and progress.