The main objective of the project is to detect the cancer in breast, lung and in bones using deep learning techniques.
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning across healthcare domains together with the availability of highly characterised cancer datasets has accelerated research into the utility of deep learning in the analysis of the complex biology of cancer. While early results are promising, this is a rapidly evolving field with new knowledge emerging in both cancer biology and deep learning. In this review, we provide an overview of emerging deep learning techniques and how they are being applied to oncology
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
SOFTWARE FRONT END REQUIREMENTS
H/W CONFIGURATION:
Processor- I3/Intel Processor
Hard Disk- 160GB
Key Board- Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
RAM - 8GB
S/W CONFIGURATION:
Operating System: Windows 7/8/10
Server side Script: HTML, CSS, Bootstrap & JS
Programming Language: Python
Libraries: Flask, Pandas, Mysql.connector, Os, Smtplib, Numpy
IDE/Workbench: PyCharm
Technology: Python 3.6+
Server Deployment: Xamp Server