Artificial Intelligence for Data-Driven Medical Diagnosis

Published by De Gruyter 2021

Artificial Intelligence for Data-Driven Medical Diagnosis

Edited by: Deepak Gupta , Utku Kose , Bao Le Nguyen and Siddhartha Bhattacharyya

Volume 3 in the series Intelligent Biomedical Data Analysis

https://doi.org/10.1515/9783110668322

Overview
Contents

About this book

This book collects research works of data-driven medical diagnosis done via Artificial Intelligence based solutions, such as Machine Learning, Deep Learning and Intelligent Optimization. Physical devices powered with Artificial Intelligence are gaining importance in diagnosis and healthcare. Medical data from different sources can also be analyzed via Artificial Intelligence techniques for more effective results.

Author / Editor information

D. Gupta, S. Bhattacharya, India, U. Kose, Turkey, and Bao Le Nguyen, Vietnam

Topics

Frontmatter Publicly Available Download PDF	I
Preface Publicly Available Download PDF	VII
Acknowledgment Publicly Available Download PDF	XI
Contents Publicly Available Download PDF	XIII
List of contributors Publicly Available Download PDF	XV
1 Performance of CNN for predicting cancerous lung nodules using LightGBM Subrato Bharati and Prajoy Podder Requires Authentication Unlicensed Licensed Download PDF	1
2 Deep learning-based cellular image analysis for intelligent medical diagnosis Kerem Delikoyun, Ersin Cine, Muge Anil-Inevi, Oyku Sarigil, Engin Ozcivici and H. Cumhur Tekin Requires Authentication Unlicensed Licensed Download PDF	19
3 Deep learning approaches in metastatic breast cancer detection Nazan Kemaloğlu, Turgay Aydoğan and Ecir Uğur Küçüksille Requires Authentication Unlicensed Licensed Download PDF	55
4 Machine learning: an ultimate solution for diagnosis and treatment of cancer Sonia Singla, G. Veeramalai, S. Aswath, Vinod Kumar Pal and Vikas Namjoshi Requires Authentication Unlicensed Licensed Download PDF	85
5 Artificial intelligence in medicine (AIM): machine learning in cancer diagnosis, prognosis and therapy Sahar Qazi, Khalid Raza and Naiyar Iqbal Requires Authentication Unlicensed Licensed Download PDF	103
6 Diagnosis disease from medical databases using neural networks: a review Omer Deperlioglu Requires Authentication Unlicensed Licensed Download PDF	127
7 A novel neutrosophic approach-based filtering and Gaussian mixture modeling clustering for CT/MR images A. Lenin Fred, H. Ajay Kumar, S. N. Kumar and Parasuraman Padmanabhan Requires Authentication Unlicensed Licensed Download PDF	143
8 Decentralized solutions for data collection and privacy in healthcare Enis Karaarslan and Enis Konacaklı Requires Authentication Unlicensed Licensed Download PDF	167
9 Navigation from conventional to intelligent healthcare: adoption of Internet of health things for noncommunicable disease screening, diagnosis, monitoring and treatment in community settings Kurubaran Ganasegeran Requires Authentication Unlicensed Licensed Download PDF	191
10 Automated gastric cancer detection and classification using machine learning Prajoy Podder, Subrato Bharati and M. Rubaiyat Hossain Mondal Requires Authentication Unlicensed Licensed Download PDF	207
11 Artificial intelligence applications for medical diagnosis and production with 3D printing technologies Bekir Aksoy, Osamah Salman, İrem Sayin and Koray Özsoy Requires Authentication Unlicensed Licensed Download PDF	225
12 Detection of breast cancer using deep neural networks with transfer learning on histopathological images Kerim Kürşat Çevik, Emre Dandil, Süleyman Uzun, Mehmet Süleyman Yildirim and Ali Osman Selvi Requires Authentication Unlicensed Licensed Download PDF	245
13 A machine vision technique-based tongue diagnosis system in Ayurveda Harshvardhan Tiwari, Shivani S. Pai, N. S. Sumanth and Arundhati S. Hegde Requires Authentication Unlicensed Licensed Download PDF	265
14 Vine copula and artificial neural network models to analyze breast cancer data Vilda Purutçuoğlu and Hajar Farnoudkia Requires Authentication Unlicensed Licensed Download PDF	287
Index Requires Authentication Unlicensed Licensed Download PDF	305

(Deutsch)

Language: English
Publisher: De Gruyter
Audience: Researchers in the fields of biomedical engineering, computer science, physicians, as well as BSc., MSc. or PhD. students.
Pages
- Front matter: 18
- Main content: 308
Illustrations
- Illustrations: 35
- Coloured Illustrations: 107
- Tables: 48
Keywords: Diagnostik; Big Data; Künstliche Intelligenz; Bioinformatik; Maschinelles Lernen

eBook

Published: February 8, 2021
ISBN: 9783110668322

Hardcover

Published: February 8, 2021
ISBN: 9783110667813