Disease detection using machine learning is revolutionizing the healthcare industry by enabling the development of systems that can automatically identify diseases with high accuracy. With access to vast amounts of medical data, including patient records, medical images, and diagnostic reports, machine learning (ML) models can learn to detect patterns associated with various diseases. This capability is particularly valuable in early detection, where timely diagnosis can significantly improve patient outcomes. Machine learning models help healthcare professionals make more accurate, faster, and data-driven decisions in areas such as radiology, pathology, and genomics.
Python is a leading programming language in this domain due to its powerful libraries for data processing, machine learning, and deep learning. Final-year projects in disease detection using machine learning give students the opportunity to work on real-world healthcare challenges, leveraging data-driven techniques to diagnose diseases like cancer, diabetes, heart disease, and infectious diseases.
• Operating System: Ubuntu 18.04 LTS 64bit / Windows 10
• Development Tools: Anaconda3 / Spyder 5.0 / Jupyter Notebook
• Language Version: Python 3.11.1
• Python ML Libraries: Scikit-Learn / Numpy / Pandas / Matplotlib / Seaborn.
• Deep Learning Frameworks: Keras / TensorFlow / PyTorch.