Beyond proofs of concept, AI deployment is often flawed!

Moving a great AI idea from concept to production is arduous; the complexity intensifies if it’s in the healthcare domain. That’s why we formed Data.AI.Healthbit, a dedicated team within Data Yakka made up of clinicians, academics, designers, engineers, and data scientists. It does one thing — the only thing: use data and artificial intelligence to create better health solutions.

To be part of this team, you need to be a hands-on doer. Here, there are no project managers or non-technical supervisors. When you reach out to this team at dataaihealthbit [AT], you’ll most likely speak directly with someone who has spent years developing data solutions for health agencies.

The Data.AI.Healthbit team is currently focused on rolling out two AI-integrated health technologies:

AEye redefines eye care with an AI-driven diagnostic platform. Affordable and efficient, it’s engineered to significantly lower the global rate of undetected, devastating diseases like the ‘silent thief of sight’—glaucoma.

PredictiveSM is a sepsis prediction system that uses machine learning to detect life-threatening conditions in patients arriving at hospital emergency departments. The system processes patient information through an algorithm trained on historical data concerning sepsis cases to generate a risk score based on their likelihood of developing sepsis.

ODS2.0 In partnership with the NSW Ministry of Health, we developed a next-generation Operational Data Store (ODS) designed to enhance patient data, provide data services to academics and NGOs, and create a pipeline for swiftly deploying ML models to improve patient care.

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