Special Sessions

SS5-AI and IoT based Techniques for Medical and Healthcare Applications

DOWNLOAD: Special Session

Session Chair/ Session Organizers:
1. Dr. S. Vijayakumar, Associate Professor, HoD of CSE(CS), IARE Hyderabad
2. Dr. Rajesh Kaluri, Associate Professor, SITE, VIT Vellore
3. Dr. Korhan Cengiz, Assistant Professor, Trakya University, Turkey
4. Dr. Bharath Bhushan, Assistant Professor, CSE, Sharada University, Greater Noida

Aim and Scope
Artificial Intelligence (AI) and internet-of-things (IoT) techniques are now very popularly used in current research medical and healthcare applications. Most recent years, AI and IoT based intelligence techniques more and more for the use of medical fields. The present medical system, AI and IoT techniques can be used for supporting the clinical decisions to handle medical diagnostics. AI and IoT intelligence based techniques can be organized in most of the medical devices, trackers and healthcare information systems. The huge amount of patient data recorded in electronic medical system (EMS) database, includes diagnosis, medical analysis, medications and lab reports analysis. Through the process of extraction, transformation and loading (ETL), researchers can generate a patient dataset, medical data, semantic recognition and medical testing analysis. This results analysis can be carried for optimizing the patients diagnosis by the clinical centres. Here, AI and IoT, bigdata technologies, machine learning, deep learning, edge computing, cloud computing and block chain technologies have been intelligently applied with various applications in networking, medical diagnosis and healthcare applications, shipping to build efficient, sustainable systems and intelligent solutions to medical and healthcare application systems. This special issue consider about the advanced techniques in signal processing & analysis, modelling, and classification, applied to a variety of medical diagnostic problems. Biomedical image analysis play a vital role in most of research fields and clinical practices. Very rarely the convolution of these data and their huge amount makes it essential to analyzes the widen advanced techniques. Furthermore, the introduction of new techniques and methodologies for diagnostic purposes, especially in the field of medical imaging analysis, involves innovative signal processing and machine learning approaches. The recent progress in machine learning techniques, and in particular deep learning, has revolutionized various fields of artificial vision, significantly pushing the state of the art of artificial vision systems into a wide range of high-level tasks. Such progress can help address problems in the analysis of biomedical data. This proposal inviting the original work as following research area's:

Sub Topics:

• AI and IoT applied in medical domain
• AI approaches for medical/clinical data
• Organizational data analysis using AI techniques
• IoT based medical assets analysis using AI techniques
• Elegant IoT devices design in clinical data analysis
• AI and IoT based applications for sustainable clinical services
• AI based solutions for Healthcare Systems
• Medical data integration using AI methodologies
• IoT based medical image analysis using AI system
• Neuro computing for Medical Image analysis
• AI approaches in COVID-19
• Data mining and knowledge finding in healthcare system
• Medical expert systems
• Intelligent computing and platforms for medical analysis
• COVID-19 analysis using pattern recognition
• Medical imagery analysis using computer vision for COVID-19

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