Predictive Modeling in Biomedical Data Mining and Analysis (Paperback)

1. Introduction to Biomedical Data and Data Mining Techniques
2. Opportunities and Obstacles for Machine Learning in Biomedical Application
3. Supervised Learning Approaches with Goal of Prediction of Labels or Outcomes
4. The Impact of Machine Learning in Treating Disease and Developing New Treatments
5. Information Retrieval in Biomedical Text Mining Tasks and Applications
6. Data Mining with Deep Learning in Biomedical Data
7. Enhancement in Biomedical Engineering via Data Mining
8. The Impact of Deep Machine Learning in Large Data Sets
9. Image Pre-Processing and Enhancement for Better Prediction
10. Semiautomatic/Full Automatic Normal or Abnormal Tissue Segmentation
11. Mathematical Models of Supervised Learning and Application to Medical Diagnosis
12. Deep Neural Network in Biomedical Image Segmentation and Processing
13. Clinical Decision-Making and Predicting Patient Trajectories
14. Deep Transfer Learning and NCA-based Multimodal Brain Tumor Classification
15. Addressing Challenges and Roadblocks in Biomedical Data with Reference to the Data-Driven Machine Learning