Getting the correct diagnosis as soon as possible, without unnecessary tests or trials of failed treatment, is the goal and hallmark of excellent healthcare. Clinical reasoning is central to the goal of rapidly deducing the correct clinical diagnosis whilst continuing to be safe and careful. This reasoning is also required to make optimal, patient-centred decisions afterwards.Commonplace healthcare and training are far from attaining this goal. Inability to correctly diagnose patients is often accompanied by mistakes, wastage, and sometimes allegations of medical malpractice. Some countries like the USA have great wealth and advanced technology, yet consistently have poor overall outcomes and significant medicolegal litigation. Healthcare training is fragmented and flawed, with multiple styles and approaches without any unifying, clear path for learners.This book aims to address all of those limitations.Clinical reasoning is defined in a universal, simple and practical manner for all healthcare trainees, professionals and leaders. The learning journey for this skill is described, and applies for any patient in any setting. In so doing, this method aims to accelerate the acquisition of competence, and increase the extent of achieved competence.

Clinical reasoning is an essential non-negotiable element for all health professionals. The ability of the health professional to demonstrate professional competence, compassion, and accountability depend on a foundation of sound clinical reasoning. The clinical reasoning process needs to bring together knowledge, experience, and understanding of people, the environment, and organizations along with a strong moral compass in making sound decisions and taking necessary actions. While clinical reasoning and the role of mentors has been a focus of the continued growth and development of residency programs in physical therapy, there is a critical need to have a broader, in-depth look at how educators across academic and clinical settings intentionally facilitate the development of clinical reasoning skills across one’s career. Clinical Reasoning and Decision Making in Physical Therapy: Facilitation, Assessment, and Implementation fills this need by providing a comprehensive and in-depth focus on development of the patient-client management skills of clinical reasoning and clinical decision-making. It takes into account teaching and learning strategies, assessment, and technological applications across the continuum from novice to residents/fellows-in-training, along with academic and clinical faculty for both entry-level and specialist practice. Drs. Gina Maria Musolino and Gail Jensen have designed this comprehensive resource with contributions from professional colleagues. The text centers on life-long learning by encouraging the development of clinical reasoning abilities from professional education through residency education. The aim and scope of the text is directed for physical therapy education, to enhance clinical reasoning and clinical decision-making for developing professionals and post-professionals in both clinical and academic realms, and for the development of clinical and academic faculty. Clinical Reasoning and Decision Making in Physical Therapy uniquely offers both evidence-based approaches and pragmatic consultation from award-winning authors with direct practice experiences developing and implementing clinical reasoning/clinical decision-making in practice applications for teaching students, residents, patients, and clinical/academic faculty in classrooms, clinics, and through simulation and telehealth. Clinical Reasoning and Decision Making in Physical Therapy is the first of its kind to address this foundational element for practice that is key for real-world practice and continuing competence as a health care professional. Physical therapy and physical therapist assistant students, faculty, and clinicians will find this to be an invaluable resource to enhance their clinical reasoning and decision making abilities.

It offers the perfect balance of maternal and child nursing care with the right depth and breadth of coverage for students in today’s maternity/pediatric courses. A unique emphasis on optimizing outcomes, evidence-based practice, and research supports the goal of caring for women, families and children, not only in traditional hospital settings, but also wherever they live, work, study, or play. Clear, concise, and easy to follow, the content is organized around four major themes, holistic care, critical thinking, validating practice, and tools for care that help students to learn and apply the material.

This volume presents the proceedings of the Fourth International Conference on the Development of Biomedical Engineering in Vietnam which was held in Ho Chi Minh City as a Mega-conference. It is kicked off by the Regenerative Medicine Conference with the theme “BUILDING A FACE” USING A REGENERATIVE MEDICINE APPROACH”, endorsed mainly by the Tissue Engineering and Regenerative Medicine International Society (TERMIS). It is followed by the Computational Medicine Conference, endorsed mainly by the Computational Surgery International Network (COSINE) and the Computational Molecular Medicine of German National Funding Agency; and the General Biomedical Engineering Conference, endorsed mainly by the International Federation for Medical and Biological Engineering (IFMBE). It featured the contributions of 435 scientists from 30 countries, including: Australia, Austria, Belgium, Canada, China, Finland, France, Germany, Hungary, India, Iran, Italy, Japan, Jordan, Korea, Malaysia, Netherlands, Pakistan, Poland, Russian Federation, Singapore, Spain, Switzerland, Taiwan, Turkey, Ukraine, United Kingdom, United States, Uruguay and Viet Nam.

Comprehensive Biomedical Physics, Ten Volume Set is a new reference work that provides the first point of entry to the literature for all scientists interested in biomedical physics. It is of particularly use for graduate and postgraduate students in the areas of medical biophysics. This Work is indispensable to all serious readers in this interdisciplinary area where physics is applied in medicine and biology. Written by leading scientists who have evaluated and summarized the most important methods, principles, technologies and data within the field, Comprehensive Biomedical Physics is a vital addition to the reference libraries of those working within the areas of medical imaging, radiation sources, detectors, biology, safety and therapy, physiology, and pharmacology as well as in the treatment of different clinical conditions and bioinformatics. This Work will be valuable to students working in all aspect of medical biophysics, including medical imaging and biomedical radiation science and therapy, physiology, pharmacology and treatment of clinical conditions and bioinformatics. The most comprehensive work on biomedical physics ever published Covers one of the fastest growing areas in the physical sciences, including interdisciplinary areas ranging from advanced nuclear physics and quantum mechanics through mathematics to molecular biology and medicine Contains 1800 illustrations, all in full color

Inthesummerof2008,reinforcementlearningresearchersfromaroundtheworld gathered in the north of France for a week of talks and discussions on reinfor- ment learning, on how it could be made more e?cient, applied to a broader range of applications, and utilized at more abstract and symbolic levels. As a participant in this 8th European Workshop on Reinforcement Learning, I was struck by both the quality and quantity of the presentations. There were four full days of short talks, over 50 in all, far more than there have been at any p- vious meeting on reinforcement learning in Europe, or indeed, anywhere else in the world. There was an air of excitement as substantial progress was reported in many areas including Computer Go, robotics, and ?tted methods. Overall, the work reported seemed to me to be an excellent, broad, and representative sample of cutting-edge reinforcement learning research. Some of the best of it is collected and published in this volume. The workshopandthe paperscollectedhere provideevidence thatthe ?eldof reinforcement learning remains vigorous and varied. It is appropriate to re?ect on some of the reasons for this. One is that the ?eld remains focused on a pr- lem — sequential decision making — without prejudice as to solution methods. Another is the existence of a common terminology and body of theory.

KES International (KES) is a worldwide organisation that provides a professional community and association for researchers, originally in the discipline of Kno- edge Based and Intelligent Engineering Systems, but now extending into other related areas. Through this, KES provides its members with opportunities for publication and beneficial interaction. The focus of KES is research and technology transfer in the area of Intelligent Systems, i.e. computer-based software systems that operate in a manner analogous to the human brain, in order to perform advanced tasks. Recently KES has started to extend its area of interest to encompass the contribution that intelligent systems can make to sustainability and renewable energy, and also the knowledge transfer, innovation and enterprise agenda. Involving several thousand researchers, managers and engineers drawn from universities and companies world-wide, KES is in an excellent position to faci- tate international research co-operation and generate synergy in the area of arti- cial intelligence applied to real-world ‘Smart’ systems and the underlying related theory. The KES annual conference covers a broad spectrum of intelligent systems t- ics and attracts several hundred delegates from a range of countries round the world. KES also organises symposia on specific technical topics, for example, Agent and Multi Agent Systems, Intelligent Decision Technologies, Intelligent Interactive Multimedia Systems and Services, Sustainability in Energy and Bui- ings and Innovations through Knowledge Transfer. KES is responsible for two peer-reviewed journals, the International Journal of Knowledge based and Intel- gent Engineering Systems, and Intelligent Decision Technologies: an International Journal.

Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare. Authors Kerrie Holley, former Google healthcare professionals, guide you through the transformative potential of large language models (LLMs) and generative AI in healthcare. From personalized patient care and clinical decision support to drug discovery and public health applications, this comprehensive exploration covers real-world uses and future possibilities of LLMs and generative AI in healthcare. With this book, you will: Understand the promise and challenges of LLMs in healthcare Learn the inner workings of LLMs and generative AI Explore automation of healthcare use cases for improved operations and patient care using LLMs Dive into patient experiences and clinical decision-making using generative AI Review future applications in pharmaceutical R&D, public health, and genomics Understand ethical considerations and responsible development of LLMs in healthcare "The authors illustrate generative's impact on drug development, presenting real-world examples of its ability to accelerate processes and improve outcomes across the pharmaceutical industry."--Harsh Pandey, VP, Data Analytics & Business Insights, Medidata-Dassault Kerrie Holley is a retired Google tech executive, IBM Fellow, and VP/CTO at Cisco. Holley's extensive experience includes serving as the first Technology Fellow at United Health Group (UHG), Optum, where he focused on advancing and applying AI, deep learning, and natural language processing in healthcare. Manish Mathur brings over two decades of expertise at the crossroads of healthcare and technology. A former executive at Google and Johnson & Johnson, he now serves as an independent consultant and advisor. He guides payers, providers, and life sciences companies in crafting cutting-edge healthcare solutions.

Still the #1 resource for today’s pediatric ICU teams, Pediatric Critical Care, 5th Edition covers the entire field, from basic science to cutting-edge clinical applications. Drs. Bradley P. Fuhrman and Jerry J. Zimmerman, accompanied by an expert team of editors and contributors from around the world, bring you today’s best information on the current and future landscape of pediatric critical care so you can consistently deliver optimum care to your young patients. Boasts highly readable, concise chapters with hundreds of useful photos, diagrams, algorithms, and clinical pearls. Clear, logical, organ-system approach allows you to focus on the development, function, and treatment of a wide range of disease entities. Includes new content on the expanding use of ultrasound at the bedside and the increase in nursing responsibilities in the PICU. Eighteen new chapters cover topics such as delirium, metabolism, endocrinology, nutrition, nursing, and much more. Features expanded and updated information on critical communication, professionalism, long-term outcomes, palliative care, ultrasonography, PCCM in resource-limited settings, ventilator-induced lung injury, non-invasive ventilation, updated CNS pathophysiology, the ‘Erythron’, and immunity and infection.

This Research Topic is the fourth volume of the series Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine Volume I: Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume I Volume II:Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume II Volume III:Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume III Analytics based on artificial intelligence has greatly advanced scientific research fields like natural language processing and imaging classification. Clinical research has also greatly benefited from artificial intelligence. Emergency and critical care physicians face patients with rapidly changing conditions, which require accurate risk stratification and initiation of rescue therapy. Furthermore, critically ill patients, such as those with sepsis, acute respiratory distress syndrome, and trauma, are comprised of heterogeneous population. The “one-size-fit-all” paradigm may not fit for the management of such heterogeneous patient population. Thus, artificial intelligence can be employed to identify novel subphenotypes of these patients. These sub classifications can provide not only prognostic value for risk stratification but also predictive value for individualized treatment. With the development of transcriptome providing a large amount of information for an individual, artificial intelligence can greatly help to identify useful information from high dimensional data. Altogether, it is of great importance to further utilize artificial intelligence in the management of critically ill patients.