Bentham Science Publishers

Congenital heart defects (CHD) are the most frequent malformation in the human fetus and are the leading cause of mortality due to malformations in the first year of life. Despite its clinical importance screening performed by ultrasonographic examination during the second trimester of pregnancy has shown disappointingly low detection rates mainly due to the difficulties in obtaining an adequate examination of the fetal heart. Four-dimensional (4D) ultrasound of the fetal heart has been recently suggested as a tool to improve the detection rate of CHD by decreasing the dependency on operator skills required in two-dimensional ultrasound scans but up to now no practical manuals are available in describing its application in clinical practice for the study of fetal heart. The objective of this Ebook is to explain the role of 4D during second trimester examination and in fetuses with CHD. T

This reference demonstrates the development of a context aware decision-making health informatics system with the objective to automate the analysis of human centric wellness and assist medical decision-making in healthcare.

The book introduces readers to the basics of a clinical decision support system. This is followed by chapters that explain how to analyze healthcare data for anomaly detection and clinical correlations. The next two sections cover machine learning techniques for object detection and a case study for hemorrhage detection. These sections aim to expand the understanding of simple and advanced neural networks in health informatics. The authors also explore how machine learning model choices based on context can assist medical professionals in different scenarios.

Key Features :

-Reader-friendly format with clear headings, introductions and summaries in each chapter

-Detailed references for readers who want to conduct further research

-Expert contributors providing authoritative knowledge on machine learning techniques and human-centric wellness

-Practical applications of data science in healthcare designed to solve problems and enhance patient wellbeing

-Deep learning use cases for different medical conditions including hemorrhages, gallbladder stones and diabetic retinopathy

Demonstrations of fast and efficient CNN models with varying parameters such as Single shot detector, R-CNN, Mask R-CNN, modified contrast enhancement and improved LSTM models.

This reference is intended as a primary resource for professionals, researchers, software developers and technicians working in healthcare informatics systems and medical diagnostics. It also serves as a supplementary resource for learners in bioinformatics, biomedical engineering and medical informatics programs and anyone who requires technical knowledge about algorithms in medical decision support systems.

Artificial intelligence (AI) is viewed as one of the technological advances that will reshape modern societies and their relations. While the design and deployment of systems that continually adapt hold the promise of far-reaching, positive change, they simultaneously pose significant risks, especially to already vulnerable people.

This work explores the meaning of AI, and the important role of critical understanding and its phenomenological foundation in shaping its ongoing advances. The values, power, and magic of reason are central to this discussion. Critical theory has used historical hindsight to explain the patterns of power that shape our intellectual, political, economic, and social worlds, and the discourse on AI that surrounds these worlds. The authors also delve into niche topics in philosophy such as transcendental self-awareness, post-humanism, and concepts of space-time and computer logic.

By embedding a critical phenomenological orientation within their technical practices, AI communities can develop foresight and tactics that can better align research and technology development with established ethical principles — centering vulnerable people who continue to bear the brunt of the negative impacts of innovation and scientific progress. The creation of a critical–technical practice of AI will lead to a permanent revolution in social, scientific, and political communities. The years ahead will usher in a wave of new scientific breakthroughs and technologies driven by AI research, making it incumbent upon AI communities to strengthen the social contract through ethical foresight, a capability which only phenomenology can deliver, ultimately supporting future technologies that enable greater well-being, with the goal of delivering practical truths.

A Critical Understanding of Artificial Intelligence: A Phenomenological Foundation is an essential read for anyone interested in the complex debate and phenomenology surrounding AI and its growing role in our society.

The book aims to provide a deeper understanding of the synergistic impact of Artificial intelligence (AI) and the Internet of Things (IoT) for disease detection. It presents a collection of topics designed to explain methods to detect different diseases in humans and plants. Chapters are edited by experts in IT and machine learning, and are structured to make the volume accessible to a wide range of readers.

Key Features:

- 17 Chapters present information about the applications of AI and IoT in clinical medicine and plant biology

- Provides examples of algorithms for heart diseases, Alzheimer's disease, cancer, pneumonia and more

- Includes techniques to detect plant disease

- Includes information about the application of machine learning in specific imaging modalities

- Highlights the use of a variety of advanced Deep learning techniques like Mask R-CNN

- Each chapter provides an introduction and literature review and the relevant protocols to follow

The book is an informative guide for data and computer scientists working to improve disease detection techniques in medical and life sciences research. It also serves as a reference for engineers working in the healthcare delivery sector.

Abdominal pain is one of the frequent reasons for admission to emergency departments in hospitals. Diagnosis in patients presenting abdominal pain is a challenge for physicians owing to several indications, and a lack of contraindications. Delay in diagnosis and misdiagnosis is a common problem even for the most experienced emergency physician or general surgeon. Disruptions that may be related to ancillary services such as radiology and biochemistry also increase the difficulty. Abdominal Pain: Essential Diagnosis and Management in Acute Medicine is a definitive diagnosis guide that serves as a quick reference that supplements medical examinations.

It gives physicians involved in a range of medical specialties (emergency medicine, family medicine, gastroenterology, general surgery) an understanding of how to apply procedures to expediently relieve pain where possible, after evaluating and recording the initial vital signs and findings on systemic examination.

Key Features:

- Covers abdominal pain diagnosis and patient management patient in a systematic and structured manner in 12 chapters

- Chapters are dedicated to specific topics

- Presents an individualized approach tailored for the patient to address common problems

- Gives general working knowledge for specific diseases in the list of possible diagnoses

- Provides a guide to situations involving trauma and surgery

Advanced Catalysts Based on Metal-organic Frameworks is a comprehensive introduction to advanced catalysts based on MOFs. It covers basic information about MOF catalysts with industrial and environmental applications. The detailed chapters update readers on current applications and strategies to apply MOF-based catalysts in industrial processes geared for sustainability initiatives such as renewable energy, pollution control and combating carbon emissions. Key Features - 13 structured, easy to read chapters that comprehensively cover MOF catalysts - An introduction to basic information about MOF catalysts - In-depth coverage of advanced applications of MOF catalysts - Explanation of MOF modifications and applications of derivative compounds - In-depth coverage of MOF catalysts used for electrocatalysis and photocatalysis - Detailed explanation of environmental-friendly and sustainable technologies (biomass upgrading, water purification, CO2 capture) - Updated references for advanced readers The is an essential reference for chemical engineers, scientists in the manufacturing and sustainability industry and post-graduate scholars working on MOFs and chemical catalysis.

This 2 volume set aims to shed light on the various advantages and drawbacks of the same along with the opportunities and markets that are emerging because of digital transformation. This volume encompasses diverse perspectives on the digital landscape for Small and Medium Enterprises (SMEs). It delves into the use of digital tools like Big Data, IoT, AI, and ML in Chapter 1, followed by an exploration of factors influencing online shopping adoption in SMEs in Ghana (Chapter 2). Chapter 3 sheds light on the digital transformation of African SMEs, while Chapter 4 offers insights into the consequences of digitalization for SMEs in Sub-Saharan Africa. The subsequent chapters cover topics such as the impact of Big Data on SMEs' performance, digitization initiatives for African telecom service providers, the role of social media as a promotional tool for SMEs in Ghana, and the utilization of Artificial Intelligence by SMEs in Africa, addressing both benefits and challenges. The chapters provide information for educators at all levels to obtain a complete understanding of the technology-based environment that impacts teaching and commerce. It also serves as a resource for policymakers, entrepreneurs, researchers, and students interested in digital transformation in Africa.

The discovery of new materials and the manipulation of their exotic properties for device fabrication is crucial for advancing technology. Nanoscience, and the creation of nanomaterials have taken materials science and electronics to new heights for the benefit of mankind. Advanced Materials and Nanosystems: Theory and Experiment covers several topics of nanoscience research. The compiled chapters aim to update readers by highlighting modern developments in materials science theory and experiments. The significant role of new materials in future technology is also demonstrated. The book serves as a reference for curriculum development in technical institutions and research programs in the field of physics, chemistry and applied areas of science like materials science, chemical engineering and electronics.

This part covers 11 topics in these areas:

1- Role of Plasmonic Metal-semiconductor Heterostructure in Photo Catalytic Hydrolysis and Degradation of Toxic Dyes

2 -BaZrO3-Based Ceramics and Ceramic Composites as Smart Materials for Advanced Applications

3 -A High-capacity Anode Material for Lithium-ion Batteries is Sili-graphene Type SiC3

4 -An Introduction to the Fabrication of White Light-emitting Diodes

5 -Electronic and Piezoelectric Properties of Nonmetal Doped II-VI Monolayer Compounds

6- A Theoretical Investigation on the New Quaternary MAX-phase Compounds

7- Surface Segregation in Pt 3 Nb and Pt 3 Ti using Density Functional-based Methods.

8- Nanoparticles and Environmental Health

9 -Investigation for Optimum site for adsorption and population effect of Lithium on Silicene Monolayer

10- Strategies for Synthesizing Metal Oxide Nanoparticles and the Challenges

11- Heterogeneous Semiconductor Photocatalysis for Water Purification: Basic Mechanism and Advanced Strategies

The discovery of new materials and the manipulation of their exotic properties for device fabrication is crucial for advancing technology. Nanoscience, and the creation of nanomaterials have taken materials science and electronics to new heights for the benefit of mankind.Advanced Materials and Nanosystems: Theory and Experiment covers several topics of nanoscience research. The compiled chapters aim to update students, teachers, and scientists by highlighting modern developments in materials science theory and experiments. The significant role of new materials in future technology is also demonstrated. The book serves as a reference for curriculum development in technical institutions and research programs in the field of physics, chemistry and applied areas of science like materials science, chemical engineering and electronics.

This part covers 12 topics in these areas:

- Recent advancements in nanotechnology: a human health Perspective.

- An exploratory study on characteristics of SWIRL of AlGaAs/GaAs in advanced bio based nanotechnological systems.

- Electronic structure of the half-Heusler ScAuSn, LuAuSn and their superlattice.

- Recent trends in nanosystems.

- Improvement of performance of single and multicrystalline silicon solar cell using low-temperature surface passivation layer and antireflection coating.

- Advanced materials and nanosystems.

- Effect of nanostructure-materials on optical properties of some rare earth ions doped in silica matrix.

- Nd2Fe14B and SmCO5: a permanent magnet for magnetic data storage and data transfer technology.

- Visible light induced photocatalytic activity of MWCNTS decorated sulfide based nano photocatalysts.

- Organic solar cells. - Neodymium doped lithium borosilicate glasses.

- Comprehensive quantum mechanical study of structural features, reactivity, molecular properties and wave function-based characteristics of capmatinib.

Advanced Mathematical Applications in Data Science comprehensively explores the crucial role mathematics plays in the field of data science. Each chapter is contributed by scientists, researchers, and academicians. The 13 chapters cover a range of mathematical concepts utilized in data science, enabling readers to understand the intricate connection between mathematics and data analysis. The book covers diverse topics, including, machine learning models, the Kalman filter, data modeling, artificial neural networks, clustering techniques, and more, showcasing the application of advanced mathematical tools for effective data processing and analysis. With a strong emphasis on real-world applications, the book offers a deeper understanding of the foundational principles behind data analysis and its numerous interdisciplinary applications. This reference is an invaluable resource for graduate students, researchers, academicians, and learners pursuing a research career in mathematical computing or completing advanced data science courses.

Key Features:

- Comprehensive coverage of advanced mathematical concepts and techniques in data science

- Contributions from established scientists, researchers, and academicians

- Real-world case studies and practical applications of mathematical methods

- Focus on diverse areas, such as image classification, carbon emission assessment, customer churn prediction, and healthcare data analysis

- In-depth exploration of data science's connection with mathematics, computer science, and artificial intelligence

- Scholarly references for each chapter - Suitable for readers with high school-level mathematical knowledge, making it accessible to a broad audience in academia and industry.