Skip to main content

Artificial Intelligence in Biomedical and Modern Healthcare Informatics

  • 1st Edition - September 27, 2024
  • Latest edition
  • Editors: M. A. Ansari, R.S Anand, Pragati Tripathi, Rajat Mehrotra, Md Belal Bin Heyat
  • Language: English

Artificial Intelligence in Biomedical and Modern Healthcare Informatics provides a deeper understanding of the current trends in AI and machine learning within healthcare diagnosis… Read more

Description

Artificial Intelligence in Biomedical and Modern Healthcare Informatics provides a deeper understanding of the current trends in AI and machine learning within healthcare diagnosis, its practical approach in healthcare, and gives insight into different wearable sensors and its device module to help doctors and their patients in enhanced healthcare system.

The primary goal of this book is to detect difficulties and their solutions to medical practitioners for the early detection and prediction of any disease.

The 56 chapters in the volume provide beginners and experts in the medical science field with general pictures and detailed descriptions of imaging and signal processing principles and clinical applications.

With forefront applications and up-to-date analytical methods, this book captures the interests of colleagues in the medical imaging research field and is a valuable resource for healthcare professionals who wish to understand the principles and applications of signal and image processing and its related technologies in healthcare.

Key features

  • Discusses fundamental and advanced approaches as well as optimization techniques used in AI for healthcare systems
  • Includes chapters on various established imaging methods as well as emerging methods for skin cancer, brain tumor, epileptic seizures, and kidney diseases
  • Adopts a bottom-up approach and proposes recent trends in simple manner with the help of real-world examples
  • Synthesizes the existing international evidence and expert opinions on implementing decommissioning in healthcare
  • Promotes research in the field of health and hospital management in order to improve the efficiency of healthcare delivery systems

Readership

Graduate students and researchers on medical informatics, Healthcare workers and stakeholders involved in health technology 

Table of contents

1. Impact of Artificial Intelligence on Public Health: A Prospective Study on Medical Social Work Practice

2. Upshots of Healthcare with AI

3. Artificial Intelligence and Machine Learning Assisted Robotic Surgery: Current Trends and Future Scope

4. A Deep Perspective of Blockchain Applications in Healthcare Sector and Industry 4.0

5. Analyzing the role of Machine Learning Techniques in Healthcare Systems

6. Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) in Biomedical Fields: A Prospect in Improvising Medical Healthcare Systems

7. Artificial Intelligence in respiratory diseases with special insight through bioinformatics

8. Electroencephalography (EEG) and Epilepsy

9. A Review on Brain Computer Interface and its Applications

10. Recent Trends in Metabolomics and Artificial Intelligence

11. A comprehensive review on state of art imagined speech decoding techniques using Electroencephalography

12. Parkinson's Disease Diagnosis, Treatment, and Future Scope: An Epilogue

13. Recent Advances in Removal of Artefacts from EEG Signal Records

14. Computer Aided Diagnosis in Health Care: Case Study on Lung Cancer Diagnosis

15. AI and its role in predictive preclinical models for drug efficacy testing

16. Machine Learning-based Solutions for Brain Tumor Detection: Comparative Study and Limitations

17. Indoor and Home-Based Post-Stroke Rehabilitation Techniques- A Systemic Review

18. A comprehensive study on implementable antennas for medical applications

19. Deep Learning for Bone Age Assessment: Current Status and Future Prospects

20. Emerging Applications of Artificial Intelligence in Analyzing EEG Signals for the Healthcare Sector

21. Epilepsy Detection System using CWT and Deep-CNN

22. Isolated Indian Sign Language Recognition with Multihead Attention Transformer based network and Mediapipe’s landmarks

23. Diagnosis of Parkinson’s Disease based on Biological and Imaging-derived features using Machine learning and Deep learning

24. Brain Tumor and Feature Detection from MRI and CT scan using Artificial Intelligence

25. Neuromodulation via Brain Stimulation: A Promising Therapeutic Perspective for Alzheimer’s Disease

26. A Biosensor for the Detection of Viruses using One-Dimensional Photonic Crystals

27. Artificial Intelligence Based Seizure Detection Systems in Electroencephalography: Transforming Healthcare for Accurate Diagnosis and Treatment

28. Artificial Intelligence and Image Enhancement based methodologies used for detection of tumor in MRIs of human brain

29. Machine learning based workload Identification using Functional Near-Infrared Spectroscopy (fNIRS) Data

30. Forecasting the COVID-19 pandemic through the hybridization of Machine Intelligent Algorithms

31. Suppression of Noise Signals from Computed Tomography and Ultrasound Medical Images and Performance Evaluation

32. Prediction Of Non-Alcoholic Fat Liver Disease Using Machine Learning

33. Evaluation of Diabetes Classification with Machine Learning Framework

34. Various Segmentation Methods/ Techniques for Medical Images and The Role of IoT

35. Augmented Mass Detection of Breast Cancer in Mammogram Images Using Deep Intelligent Neural Network Model

36. CNC Machines in Production of Medical Devices

37. Analysis and prediction of Cardiomyopathy using Artificial Intelligence

38. A Preemptive Approach to Polycystic Ovary Syndrome Diagnosis using Machine Learning

39. Mapping the Landscape of Human Activity Recognition Techniques in Health Monitoring for Chronic Disease Management

40. Analysis and Organization of Mycological Skin Contaminations by Means of Medicinal Imagery

41. A Sensitive Biosensor for the Detection of Blood Components Using 2D Photonic Crystals

42. Machine Learning Assisted EEG Signal Classification for Automated Diagnosis of Mental Stress

43. CNN based Deep Learning model for Skin Cancer detection using Dermatoscopic Images

44. Bioelectrical Impedance Analysis Body Composition Estimation of Fat Mass Percentage in People with Spinal Cord Injury

45. Advanced EEG Signal Processing and Feature Extraction Concepts

46. Fractal Analysis on Biomedical Signal

47. Detection of Metastasis Osteosarcoma Using Deep Fuzzy Gradient Recurrent Convolutional Neural Network

48. Deep Learning Based Fatigue Detection Using Functional Connectivity

49. Brain Tumor Diagnosis Using Image Classifier

50. ISL Recognition System in Realtime using TensorFlow API

51. Exploring the Exciting Potential and Challenges of Brain-Computer Interfaces (BCI)

52. Transmission Dynamics of COVID-19 Virus Disease

53. Design of High Voltage Biphasic Pulse Generation Circuit with 3-Level Isolation Suitable for AED Applications

54. A Novel Scheme of Brain Tumor Detection from MRIs using K-Means Segmentation and Histogram Analysis

55. Analyzing Post COVID-19 Effects on Self-Consciousness and Awareness towards Health: A Neuroscience Framework

56. Crowdsourcing and Artificial Intelligence based Modeling Framework for effective Public Healthcare Informatics and Smart eHealth System

Product details

  • Edition: 1
  • Latest edition
  • Published: October 3, 2024
  • Language: English

About the editors

MA

M. A. Ansari

Dr. M.A. Ansari holds PhD degree on Signal and Imaging Processing from Indian Institute of Technology Roorkee. He has 18 years of experience in teaching and research. Currently he is Professor at School of Engineering, Gautam Buddha University, where he supervised 4 PhD and 63 MTech students to date. He authored several book chapters and published almost 30 peer-reviewed articles in international journals. Dr. Ansari main research interests are medical image coding, biomedical instrumentation and control, and digital signal and image processing.
Affiliations and expertise
Professor, School of Engineering, Gautam Buddha University, India

RA

R.S Anand

R. S. Anand received the B.E., M.E., and Ph.D. degrees from the University of Roorkee, Roorkee, India, in 1985, 1987, and 1992, respectively.,He is currently a Professor with the Electrical Engineering Department, IIT Roorkee, Roorkee. He has authored or coauthored more than 200 research papers in journals and conferences. His current research interests include medical signal and image processing, ultrasonic nondestructive evaluation (NDE), medical diagnosis, and speech signal processing.,Dr. Anand is a Life Member of the Ultrasonic Society of India.

Affiliations and expertise
Professor, Department of Electrical Engineering ,Indian Institute of Technology, Roorkee, India

PT

Pragati Tripathi

Pragati Tripathi received an M.Tech degree in power electronics from Gautam Buddha University, Greater Noida, India, in 2018. She is working as a Research Scholar with the School of Engineering, Gautam Buddha University. She has also been associated with IIT Delhi and served as a Research Associate with Sharda University, Greater Noida. Her research interests include signal processing, brain mapping, and neuroscience.
Affiliations and expertise
Biomedical Laboratory Department of Electrical Engineering, Gautam Buddha University. India

RM

Rajat Mehrotra

Rajat Mehrotra is an Assistant Professor in the Electrical & Electronics Engineering Department at GL Bajaj Institute of Technology & Management, Greater Noida, India. He received his BTech in Electrical and Electronics Engineering from the Dr. A.P.J. Abdul Kalam Technical University, Lucknow (Formerly UPTU), in 2008 and his MTech in Telecommunication Engineering from the same university, in 2014 and his PhD. in the field of Medical Image Processing. His research interests include digital image processing, biomedical imaging, and deep learning. Currently, he is involved in research with the School of Engineering at Gautam Buddha University, Greater Noida. He has published his research in various journals of international repute. He has more than 14 years of experience in teaching and research. He has also published multiple patents in his area of research.
Affiliations and expertise
Bajaj Institute of Technology ,GL Bajaj Institute of Technology & Management, Greater Noida, India

MH

Md Belal Bin Heyat

Md Belal Bin Heyat received the B.tech degree in E.I. from Integral University, Lucknow, UP, India in 2014. He is successfully completed Master of Technology degree in Electronics Circuit & System, department of electronics and communication engineering from Integral University, Lucknow, Uttar Pradesh, India in 2016. He has author and co-author in number of International journals, National journals, Symposium and Conferences. He is an editor and reviewer for three international and national journals. His research interests include electronics, communication engineering, instrumentation, therapy, medical and biomedical engineering.

Affiliations and expertise
Shenzhen University School of Computer Science and Software Engineering Shenzhen, Guangdong, China

View book on ScienceDirect

Read Artificial Intelligence in Biomedical and Modern Healthcare Informatics on ScienceDirect