I am investigating an efficient model for investigating the prediction of cardiovascular diseases using machine learning paradigm. I have to prepare these models with respect to temporal datasets. Please suggest some datasets.
From what kind of domain you want to predict such diseases? Our lab works with ECG signals to localize the Ventricular Tachycardia in the heart. Some link of the works:
1. http://www.pkgyawali.com/contents/CinC.pdf
2. https://ieeexplore.ieee.org/document/7950596/
Another recent work is accepted in AAAI Health Intelligence Workshop, but we are still awaiting for it to appear online. If you want, I can share you our local copy.
However, we use in-house dataset and thus, sadly, won't be able to share the datasets. But in near future, we are planning to share the simulated datasets. In the meantime, you could also explore the PhysioNet bank (https://www.physionet.org/physiobank/) as they have a large collection of datasets.
I was not asking about your papers. I was asking the suggestions on using different datasets for my research. Thanks for suggesting the Physionet Bank.
Dear Abdu,
Thanks for your kind suggestion. I am not working on the image processing although ECG data is required for my research. I want a data which may have some other parameters like blood sugar, cholesterol and many other parameters pertaining to heart diseases.
No matter which set of data you use...Please be aware that you working with incomplete data...One of the main reasons for this is that for example some patient can live with some parameters and other not...we are not all made from the same material... As well you are searching only primary disease and patient could day from the secondary disease...etc.