Health

Using Wi-Fi IEEE 802.11 standard, radio frequency waves are mainly used for communication on various devices such as mobile phones, laptops, and smart televisions. Apart from communication applications, the recent research in wireless technology has turned Wi-Fi into other exploration possibilities such as human activity recognition (HAR). HAR is a field of study that aims to predict motion and movement made by a person or even several people.

With the motivation of no good data sources available for all diseases (from generic to chronic) and their treatment courses, a new dataset is synthesized by exploring several medical websites and resources. It provides the precaution list corresponding to over 1000+ diaganosis. prec\_t.csv : (did, diagnose, pid) = (Disease identifier, Disease name, treatment course). This dataset can be utilized for many machine learning or deep learning based healthcare applications.

It contains the data of four omic profiles (CNV, mRNA, miRNA, and protein) obtained for BRCA, LGG, and LUAD obtained from the TCGA project. 

In addition, we provide synthetic data for a mixture of isotropic distributions.

Recent advances in computational power availibility and cloud computing has prompted extensive research in epileptic seizure detection and prediction. EEG (electroencephalogram) datasets from ‘Dept. of Epileptology, Univ. of Bonn’ and ‘CHB-MIT Scalp EEG Database’ are publically available datasets which are the most sought after amongst researchers. Bonn dataset is very small compared to CHB-MIT. But still researchers prefer Bonn as it is in simple '.txt' format. The dataset being published here is a preprocessed form of CHB-MIT. The dataset is available in '.csv' format.