Biomedical data analysis and processing using explainable (XAI) and responsive artificial intelligence (RAI) / Aditya Khamparia, Deepak Gupta, Ashish Khanna, Valentina E. Balas, editors
Optimal Boosting Label Weighting Extreme Learning Machine for Mental Disorder Prediction and Classification -- Modeling of Explainable Artificial Intelligence with Correlation based Feature Selection Approach for Biomedical Data Analysis -- Explainable machine learning model for diagnosis of Parkinson disorder -- Explainable Artificial Intelligence with Metaheuristic Feature Selection Technique for Biomedical Data Classification -- Explainable AI in Neural Networks using Shapley Values -- Design of Multimodal Fusion based Deep Learning Approach for COVID-19 Diagnosis using Chest X-Ray Images
Summary
The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as well as negative findings obtained by explainable AI techniques. It features real time experiences by physicians and medical staff for applied deep learning based solutions. The book will be extremely useful for researchers and practitioners in advancing their studies
