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Principles and Methods of Explainable Artificial Intelligence in Healthcare
Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model’s adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare m...
Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems
Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems explains the emerging technology that currently drives computer-aided diagnosis, medical analysis and other electronic healthcare systems. 11 book chapters cover advances in biomedical engineering fields achieved through deep learning and soft-computing techniques. Readers are given a fresh perspective on the impact on the outcomes for healthcare professionals who are assisted by advanced computing algorithms. Key Features: - Covers emerging technologies in biomedical engineering and healthcare that assist physicians in diagnosis, treatment, and surgical planning in a multidisciplinar...
Applications of artificial intelligence, machine learning, and deep learning in plant breeding
Artificial Intelligence (AI) is an extensive concept that can be interpreted as a concentration on designing computer programs to train machines to accomplish functions like or better than hu-mans. An important subset of AI is Machine Learning (ML), in which a computer is provided with the capacity to learn its own patterns instead of the patterns and restrictions set by a human programmer, thus improving from experience. Deep Learning (DL), as a class of ML techniques, employs multilayered neural networks. The application of AI to plant science research is new and has grown significantly in recent years due to developments in calculation power, proficien-cies of hardware, and software progr...
Big Data and Edge Intelligence for Enhanced Cyber Defense
An unfortunate outcome of the growth of the Internet and mobile technologies has been the challenge of countering cybercrime. This book introduces and explains the latest trends and techniques of edge artificial intelligence (EdgeAI) intended to help cyber security experts design robust cyber defense systems (CDS), including host-based and network-based intrusion detection system and digital forensic intelligence. This book discusses the direct confluence of EdgeAI with big data, as well as demonstrating detailed reviews of recent cyber threats and their countermeasure. It provides computational intelligence techniques and automated reasoning models capable of fast training and timely data p...
Pests and Diseases Monitoring and Forecasting Algorithms, Technologies, and Applications
Plant pests and diseases cause an annual average of 40% global food failure addressed by FAO and more than 100 billion dollars in loss of forest and grass resources. Scientific prevention and control of pests and diseases in agriculture, forestry and grass is important to ensure food security, ecological and environmental safety, etc. At present, the accuracy of individual identification of agricultural, forestry and grass pests and diseases are low, making it difficult to achieve accurate outpost warning, occurrence environment monitoring and multiple pest and disease type differentiation, resulting in the inability to achieve early detection and control of pests and diseases. With the rapi...
IOT with Smart Systems
This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining and software analysis. It presents the outcomes of the Sixth International Conference on Information and Communication Technology for Intelligent Systems (ICTIS 2022), held in Ahmedabad, India. The book is divided into two volumes. It discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike.
Advanced AI Methods for Plant Disease and Pest Recognition
Plant diseases and pests cause significant losses to farmers and threaten food security worldwide. Monitoring the growing conditions of crops and detecting plant diseases is critical for sustainable agriculture. Traditionally, crop inspection has been carried out by people with expert knowledge in the field. However, regarding any activity carried out by humans, this activity is prone to errors, leading to possible incorrect decisions. Innovation is, therefore, an essential fact of modern agriculture. In this context, deep learning has played a key role in solving complicated applications with increasing accuracy over time, and recent interest in this type of technology has prompted its potential application to address complex problems in agriculture, such as plant disease and pest recognition. Although substantial progress has been made in the area, several challenges still remain, especially those that limit systems to operate in real-world scenarios.
