At aimedica.app, our mission is clear: to leverage the prowess of AI to revolutionize the medical diagnosis, empower doctors, and enhance patient care. With our in-house technology, Confidence AI, we are driving the innovation. This is the story of how we reached remarkable accuracy by emphasizing the error associated with each prediction. In the medical field, reaching high accuracy is critical, as the cost of wrong predictions is high. By remaining transparent where our AI can provide predictions, we can maintain high trust for doctors and patients.

Into the Heart Disease Dataset

At the heart of our journey lies a comprehensive dataset spanning over three decades. Dating back to 1988, this dataset comprises four distinct databases—Cleveland, Hungary, Switzerland, and Long Beach V. Within these databases, a treasure trove of 76 attributes awaits, each holding a piece of the diagnostic puzzle. The "target" field, classifies patients into two categories: those free from heart disease (encoded as 0) and those with the condition (encoded as 1).

Going deeper, we encounter attributes that range from patient demographics such as age and sex, to physiological metrics like resting blood pressure, serum cholesterol levels, and maximum heart rate achieved. This intricate mosaic of data forms the bedrock upon which our AI-powered diagnostic model is built.

Note: The data seems well prepared: variables are distributed with a high information ratio and irrelevantly correlated.

Confidence AI: Precision and Transparency

In the dynamic realm of medical technology, certainty is non-negotiable. With Confidence AI, our proprietary technology we redefine how we approach diagnostics — it's about quantifying the confidence behind each one. We imagine a diagnosis not as a binary output, but also as a value defining confidence in judgment. Confidence AI, our model, not only provides predictions but also insights of certainty in predictions. This transparency is a game-changer, as doctors can now make informed decisions backed by a quantifiable level of confidence.

Results: The confidence AI model reached 100% accuracy on a testing sample by eliminating 20% uncertain predictions. Without eliminating uncertain predictions accuracy at a level 80% was reached.

Conclusion: Safe Prediction for Diagnostics

As we stand at the intersection of AI and medicine, aimedica.app's commitment to innovation has birthed a new era of diagnostics. Heart disease uses cases of Confidence AI exemplifies how our technology can be applied. We believe that the future of medical technology rests upon the pillars of precision & transparency, which we can provide.