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Project Gravitar

Predicting pregnancy disorders such as gestational diabetes mellitus (GDM) and hypertensive disorders in pregnancy (HDP) within the first trimester to allow for early intervention.


Team members:

  • Rishikha Thangavelu, Bachelor of Applied Data Science Advanced (Honours)

  • Maitri Justitian, Bachelor of Electrical and Computer System Engineering 

  • Emma Poon, Bachelor of Medical Science and Doctor of Medicine 


  • Lisa Moran

  • Joanne Enticott

  • Siew Lim

Affiliation: Monash Centre for Health Research and Implementation (MCHRI)

Project History

Project Gravitar was created during the MYMI HISS program of 2021/2022, a 12-week intensive program backed by MYMI, MIME and Monash Partners.

Progress you’ve made:

  • During the program, we adopted the Biodesign Innovation Process.

  • We validated the clinical gap in the medical pathway of predicting the pregnancies disorders 


Achievements so far:

  • Our team has successfully made a machine learning prediction model for GDM with an accuracy of 84% and AUC of 0.92.


Current stage of the project:

  • Looking into a new library with potential of giving a better accuracy for the prediction model (for both GDM and HDP)

  • Developing HDP prediction model 


  • Model Development for HDP prediction

  • App design

    • Further development of wire frame

    • Risk perception and communication 

  • Web-App Development

    • Develop the wireframe into a working web-app

    • Integrate prediction model into the app 

  • Internal Pilot Trial


We plan on conducting a fortnightly meeting to update each team members on each other’s progress as we will be dividing our roles. We will also have a separate meeting with our clinicians to update them of our overall progress and gain feedback.

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