Gary Tse – författare

Internet of Things and Machine Learning for?Type I and Type II Diabetes: Use Cases provides a medium of exchange of expertise and addresses the concerns, needs, and problems associated with Type I and Type II diabetes. Expert contributions come from researchers across biomedical, data mining, and deep learning. This is an essential resource for both the AI and Biomedical research community, crossing various sectors for broad coverage of the concepts, themes, and instrumentalities of this important and evolving area. Coverage includes IoT, AI, Deep Learning, Machine Learning and Big Data Analytics for diabetes and health informatics.

Integrates many Machine learning techniques in biomedical domain to detect various types of diabetes to utilizing large volumes of available diabetes-related data for extracting knowledgeIt integrates data mining and IoT techniques to monitor diabetes patients using their medical records (HER) and administrative dataIncludes clinical applications to highlight contemporary use of these machine learning algorithms and artificial intelligence-driven models beyond research settings

Aging and Troponin: Clinical Implications and Uses Beyond Diagnosis examines the multifaceted role of troponin in clinical medicine, with a special focus on aging. This comprehensive reference provides essential technical knowledge, diagnostic and prognostic applications, and model development insights from leading experts in clinical biochemistry, pathology, and epidemiology. The book emphasizes the impact of aging on troponin test results and their interpretation, addressing age-related disorders such as renal failure. Sections cover the technical aspects of troponin assays, comparing traditional and high-sensitivity assays and exploring point-of-care testing advancements.The book also examine age-related changes and intra- and inter-individual variability in troponin levels, focuses on diagnostic applications, including troponin as a biomarker for cardiac injury and dysfunction, and the effects of age, sex, and renal impairment on diagnostic sensitivity and specificity, and discusses troponin's prognostic value for mortality in various conditions, including heart disease, sepsis, and COVID-19, and its role as a marker of organ biological age. The final section offers cutting-edge insights into the clinical applicability of troponin testing, highlighting the benefits of incorporating high-sensitivity assays into clinical workflows and providing perspectives and age-related considerations from practicing physicians on implementation and evidence-based practice.Explores how aging affects troponin levels and their interpretation in various medical conditionsDetails high-sensitivity assays and point-of-care testing tailored for elderly patientsHighlights troponin's role in predicting mortality and cardiovascular events in older adultsExamines troponin variants as indicators of muscle quality and aging-related changesOffers strategies for integrating age-adjusted troponin testing into clinical practice

This book provides a comprehensive overview of cutting-edge technologies in the diagnosis of multiple cardiovascular disease. Readers will understand technical advancements and research gaps, which will help them to optimize the design of algorithms and devices.Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases: Towards Data-Driven Smart Healthcare provides details on the adoption and implementation of advanced diagnostic techniques in different clinical settings, including population screening, clinical diagnosis, risk prediction, data-driven diagnosis, and remote healthcare monitoring. It also covers various cardiovascular diseases, from the macrovascular to microvascular levels, where early and accurate diagnosis is a high clinical need, for example, stroke, intracranial atherosclerosis, coronary artery disease, and microvascular dysfunction. The book is a practical guide with case studies, and the authors cover a wide range of cutting-edge diagnostic techniques, including artificial intelligence, radiological imaging, wearable sensors, genetic biomarkers, and multi-omics data integration. It summarizes the potentials, challenges, and ethical concerns in the implementation of these techniques under current clinical settings. It also discusses the future directions and perspectives for next-generation diagnostics based on AI-enhanced multimodal data fusion.This book targets a mixed audience of data scientists, engineers, clinicians, researchers, academics, and students interested in cutting-edge technologies, methodologies, and practices in the diagnostics of cardiovascular diseases to resolve the challenging gaps in healthcare and clinical applications.

This book provides a detailed update on all aspects of fine-needle aspiration cytology of breast lesions. In addition, the impact of molecular classification of breast cancers on cytologic diagnosis is explored, and the use of molecular techniques and artificial intelligence in diagnostic cytology is discussed.

This book provides a detailed update on all aspects of fine-needle aspiration cytology of breast lesions. In addition, the impact of molecular classification of breast cancers on cytologic diagnosis is explored, and the use of molecular techniques and artificial intelligence in diagnostic cytology is discussed.

The book "Advanced wearable sensing in clinical practice towards healthcare 5.0" provides an overview of the state of the art that caters various professionals from clinical, scientific, and engineering backgrounds, as well as the novices that are interested in wearable sensing technology. It presents a comprehensive overview of modern wearable technology and unmet challenges. The book covers research hotspots in wearable technology, including advanced materials, low-cost wearable sensing systems, bio-signal processing, multimodal data analysis, artificial intelligence, and internet-of-medical-things. The readers from various research backgrounds (e.g., biomedical engineering, artificial intelligence, material sciences, etc.) can get an in-depth understanding of current trends and future directions. It summarizes different technologies regarding the clinical needs, theoretical basis, latest technical innovations, challenges in implementation, and limitations. These details will help improve existing designs and algorithms to cater different application scenarios. The book also provides the details of the implementation of advanced wearable sensors in different clinical settings including population screening, clinical diagnosis, to remote healthcare monitoring. The targeted diseases include cardiovascular, neurological, respiratory, metabolic, and other chronic diseases. By analyzing relevant standards and regulations, the challenges for next-generation wearable sensors are discussed in the context of healthcare ecosystem from a perspective of healthcare 5.0. In summary, the book focus on technical innovations but also delves into clinical and regulatory aspects. It caters a broad spectrum of readers. Clinical researchers, healthcare professionals, and students can obtain a better grasp of current trends of wearable technology. Biomedical engineers can understand the clinical needs, the state of the art, and the challenges in implementation, to develop better wearable sensors and algorithms for signal processing and data analysis. Public health researchers and policymakers can update the regulations and clinical guidelines to enable the integration of advanced wearable sensing technologies into current healthcare ecosystems.