According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible for approximately 11% of total deaths.
This dataset is used to predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status. Each row in the data provides relavant information about the patient.
Breast cancer is the most prevalent form of cancer, with 7.8 million women surviving with the disease. Approximately 0.5-1% of breast cancers occur in men.
The dataset is from UCI ML Repository. Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image.
The National Institute on Deafness and other Communications Disorders (NIDCD) indicates that the 200-year-old American Sign Language is a complete, complex language (of which letter gestures are only part) and is the primary language for many deaf North Americans. One could implement computer vision in an inexpensive board computer like Raspberry Pi with OpenCV, and some Text-to-Speech to enabling improved and automated translation applications.
The American Sign Language letter database of hand gestures represent a multi-class problem with 24 classes of letters (excluding J and Z which require motion). The dataset format is patterned to match closely with the classic MNIST.