Brain Tumor Detection using Deep Learning Approach.

Early detection of brain tumor has an important role in further developing therapeutic outcomes, and hence functioning in endurance tolerance. Physically evaluating the various reversion imaging (magnetic resonance imaging [MRI]) images that are regularly distributed at the center is a problematic cycle. Along these lines, there is a significant need for PC-assisted strategies with improved accuracy for early detection of cancer.

Design of Smart and Secured Healthcare Service Using Deep Learning with Modified SHA-256 Algorithm.

Background: The modern era of human society has seen the rise of a different variety of diseases. The mortality rate, therefore, increases without adequate care which consequently causes wealth loss. It has become a priority of humans to take care of health and wealth in a genuine way.

Convergent learning-based model for leukemia classification from gene expression.

Microarray data analysis is a major challenging field of research in recent days. Machine learning-based automated gene data classification is an essential aspect for diagnosis of gene related any malfunctions and diseases. As the size of the data is very large, it is essential to design a suitable classifier that can process huge amount of data.