Title: Predicting Heart Disease Using Image and Numeric Data: Is it Possible?
Description: Hello everyone,
I’m currently working on a heart disease prediction system and I have a question regarding combining different types of data. Specifically, I’m interested in whether it’s possible to predict heart disease based on both medical images (such as X-rays or MRIs) and numeric/tabular data (like age, gender, cholesterol levels, blood pressure, etc.).
Has anyone worked on a similar project where they used both image processing and numeric feature analysis in the same model? What techniques or models would you recommend for handling both types of data effectively?
I would appreciate any insights or suggestions from this community. Also, if anyone has come across datasets that combine both medical images and clinical numeric data, please let me know.
Thank you!
Tags: Heart Disease Prediction, Medical Image Processing, Multimodal Data, Supervised Learning, Healthcare AI
Language: Python, TensorFlow
Product: Heart Disease Prediction Model