Computational Intelligence in Medical Decision Making and Diagnosis Techniques and Applications

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ABOUT THE BOOK

Computation intelligence (CI) paradigms, including artificial neural networks, fuzzy systems, evolutionary computing techniques, and intelligent agents, form the basis of making clinical decisions. This book explains different aspects of the current research on CI technologies applied in the field of medical diagnosis. It discusses critical issues related to medical diagnosis, like uncertainties in the medical domain, problems in the medical data, especially dealing with time-stamped data, and knowledge acquisition.

Features:

  • Introduces recent applications of new computational intelligence technologies focusing on medical diagnosis issues.
  • Reviews multidisciplinary research in health care, like data mining, medical imaging, pattern recognition, and so forth.
  • Explores intelligent systems and applications of learning in health-care challenges, along with the representation and reasoning of clinical uncertainty.
  • Addresses problems resulting from automated data collection in modern hospitals, with possible solutions to support medical decision-making systems.
  • Discusses current and emerging intelligent systems with respect to evolutionary computation and its applications in the medical domain.

This book is aimed at researchers, professionals, and graduate students in computational intelligence, signal processing, imaging, artificial intelligence, and data analytics.

TABLE OF CONTENTS

1 Prediction of Diseases Using Machine Learning Techniques

Abinash Tripathy, Panchanand Jha, Ch. Chakradhara Rao, P. Susan Lalitha Grace, P. Sharon Priya Harika, and Ch. Madhu

A Novel Virtual Medicinal Care Model for Remote Treatments

Drishti Hans, Shashi Gandhar, Gaurav Narula, Abhishek Gandhar, and Umang Hans

Artificial Intelligence in Future Telepsychiatry and Psychotherapy for E-Mental Health Revolution

Sudhir Hebbar and Vandana B

Optimized Convolutional Neural Network for Classification of Tumors from MR Brain Images

K. Ramalakshmi, R. Meena Prakash, S. Thayammal, R. Shantha Selva Kumari, and Henry Selvaraj

Predictive Modeling of Epidemic Diseases Based on Vector-Borne Diseases Using Artificial Intelligence Techniques

Inderpreet Kaur, Yogesh Kumar, Amanpreet Kaur Sandhu, and Muhammad Fazal Ijaz

Hybrid Neural Network-Based Fuzzy Inference System Combined with Machine Learning to Detect and Segment Kidney Tumor

P Srinivasa Rao, Pradeep Kumar Bheemavarapu, D Swapna, Subba Rao Polamuri, and M. Madhusudhana Subramanyam

Classification of Breast Tumor from Histopathological Images with Transfer Learning

R. Meena Prakash, K. Ramalakshmi, S. Thayammal, R. Shantha Selva Kumari, and Henry Selvaraj

Performance of IoT-Enabled Devices in Remote Health Monitoring Applications

D. Narendar Singh, Pavitra B, Ashish Singh, and Jayasimha Reddy A

Applying Machine Learning Logistic Regression Model for Predicting Diabetes in Women

Nitin Jaglal Untwal and Utku Kose

10 Compressive Sensing-Based Medical Imaging Techniques to Detect the Type of Pneumonia in Lungs

Vivek Upadhyaya, Girraj Sharma, Tien Anh Tran, and Mohammad Salim

11 Electroencephalogram (EEG) Signal Denoising Using Optimized Wavelet Transform (WT): A Study

Chaudhuri Manoj Kumar Swain, Ashish Singh, and Indrakanti Raghu

12 Predicting Diabetes in Women by Applying the Support Vector Machine (SVM) Model

Nitin Jaglal Untwal and Utku Kose

13 Data Mining Approaches on EHR System: A Survey

Thilagavathy R, Veeramani T, Deebalakshmi R, and Sundaravadivazhagan B

14 Chest Tumor Identification in Mammograms by Selected Features Employing SVM

Shivaprasad More, Pallavi Gholap, Rongxing Lu, and Sitendra Tamrakar

15 A Novel Optimum Clustering Method Using Variant of NOA

Ravi Kumar Saidala, Nagaraju Devarakonda, Thirumala Rao B, Jabez Syam, and Sujith Kumar

16 Role of Artificial Intelligence and Neural Network in the Health-Care Sector: An Important Guide for Health Prominence

Ankur Narendra Bhai Shah, Nimisha Patel, Jay A. Dave, and Rajanikanth Aluvalu

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