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This translational text offers in-depth reviews of the metabolic and nutritional disorders that are prevalent in patients with renal disease. Chapter topics address the growing epidemic of obesity and metabolic syndrome. Each chapter integrates basic and clinical approaches, from cell biology and genetics to diagnosis, patient management and treatment. Chapters in sections 4-7 include new illustrative case reports, and all chapters emphasize key concepts with chapter-ending summaries. New features also include the latest National Kidney Foundation Clinical Practice Guidelines on Nutrition i

Kidneys --- Chronic renal failure --- Diseases --- Diet therapy. --- Nutritional aspects. --- Chronic kidney failure --- Chronic renal insufficiency --- End-stage kidney disease --- End-stage renal disease --- ESRD (Disease) --- Kidney failure, Chronic --- Renal failure, Chronic --- Renal insufficiency --- Renal insufficiency, Chronic --- Abdomen --- Urinary organs --- Nephrology

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Chronic renal failure. --- Chronic kidney failure --- Chronic renal insufficiency --- End-stage kidney disease --- End-stage renal disease --- ESRD (Disease) --- Kidney failure, Chronic --- Renal failure, Chronic --- Renal insufficiency --- Renal insufficiency, Chronic --- Diseases --- Kidneys

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Chronic kidney disease is an increasing health and economical problem in our world. Obesity and diabetes mellitus, the two most common cause of CKD, are becoming epidemic in our societies. Education on healthy lifestyle and diet is becoming more and more important for reducing the number of type 2 diabetics and patients with hypertension. Education of our patients is also crucial for successful maintenance therapy. There are, however, certain other factors leading to CKD, for instance the genetic predisposition in the case of polycystic kidney disease or type 1 diabetes, where education alone is not enough.

Chronic renal failure. --- Chronic kidney failure --- Chronic renal insufficiency --- End-stage kidney disease --- End-stage renal disease --- ESRD (Disease) --- Kidney failure, Chronic --- Renal failure, Chronic --- Renal insufficiency --- Renal insufficiency, Chronic --- Diseases --- Kidneys --- Renal medicine & nephrology

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When the kidney fails its intended mission to manage the body’s waste products, physicians must perform multi-level and simultaneous adjustments to replicate kidney function. The management of the body’s absorption, reabsorption, utilization and excretion of calcium and phosphate requires constant fine tuning. Calcium and Phosphate Metabolism Management in Chronic Renal Diseases provides an overview of the state-of-the-art clinical and basic science aspects of abnormal calcium and phosphate metabolism and its management. Chen Hsing Hsu is a Professor of Internal Medicine at the University of Michigan Medical Center, Ann Arbor, Michigan.

Calcium --- Phosphates --- Chronic renal failure. --- Metabolism. --- Chronic kidney failure --- Chronic renal insufficiency --- End-stage kidney disease --- End-stage renal disease --- ESRD (Disease) --- Kidney failure, Chronic --- Renal failure, Chronic --- Renal insufficiency --- Renal insufficiency, Chronic --- Diseases --- Kidneys --- Bone products --- Calcium metabolism --- Nephrology. --- Orthopedics. --- Endocrinology. --- Internal medicine --- Hormones --- Orthopaedics --- Orthopedia --- Surgery --- Endocrinology .

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Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances in the sharing of medical information result in better and earlier diagnoses as well as more patient-tailored treatments, information management is also affected by trends such as increased patient centricity (with shared decision making), self-care (e.g., using wearables), and integrated care delivery. The delivery of health services is being revolutionized through the sharing and integration of health data across organizational boundaries. Via data science, researchers can deliver new approaches to merge, analyze, and process complex data and gain more actionable insights, understanding, and knowledge at the individual and population levels. This Special Issue focuses on how data science is used in healthcare (e.g., through predictive modeling) and on related topics, such as data sharing and data management.

data sharing --- data management --- data science --- big data --- healthcare --- depression --- psychological treatment --- task sharing --- primary care --- pilot study --- non-specialist health worker --- training --- digital technology --- mental health --- COVID-19 --- SARS-CoV-2 --- pneumonia --- computed tomography --- case fatality rate --- social distancing --- smoking --- metabolically healthy obese phenotype --- metabolic syndrome --- obesity --- coronavirus --- machine learning --- social media --- apache spark --- Twitter --- Arabic language --- distributed computing --- smart cities --- smart healthcare --- smart governance --- Triple Bottom Line (TBL) --- thoracic pain --- tree classification --- cross-validation --- hand-foot-and-mouth disease --- early-warning model --- neural network --- genetic algorithm --- sentinel surveillance system --- outbreak prediction --- artificial intelligence --- vascular access surveillance --- arteriovenous fistula --- end stage kidney disease --- dialysis --- kidney failure --- chronic kidney disease (CKD) --- end-stage kidney disease (ESKD) --- kidney replacement therapy (KRT) --- risk prediction --- naïve Bayes classifiers --- precision medicine --- machine learning models --- data exploratory techniques --- breast cancer diagnosis --- tumors classification --- n/a --- naïve Bayes classifiers