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The very rapid pace of advances in biomedical research promises us a wide range of new drugs, medical devices, and clinical procedures. The extent to which these discoveries will benefit the public, however, depends in large part on the methods we choose for developing and testing them. Modern Methods of Clinical Investigation focuses on strategies for clinical evaluation and their role in uncovering the actual benefits and risks of medical innovation. Essays explore differences in our current systems for evaluating drugs, medical devices, and clinical procedures; health insurance databases as a tool for assessing treatment outcomes; the role of the medical profession, the Food and Drug Administration, and industry in stimulating the use of evaluative methods; and more. This book will be of special interest to policymakers, regulators, executives in the medical industry, clinical researchers, and physicians.
June 21-22, 2018 Rome, Italy Key Topics : Pre-Clinical and Clinical Trials, Adverse Drug Reactions, Pharmacovigilance and Risk Management, Good Pharmacovigilance Practice, Pharmacy Practices and its Challenges, Biopharmaceutical Sciences, Clinical Trials on Various Disorders, Data Quality Management and Analysis, Pharmacovigilance Significance & Scope, Diversity in Industrial Clinical Trials and Clinical Research, Clinical Research and Statistics, Case Report in Clinical Trials, Drug Safety, Clinical Data Base Management, PV Consultings and Business Opportunity, Regulatory Affairs, Entrepreneurs Investment Meet,
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
June 07-08, 2017 Milan,. Italy Key Topics : Medicinal Chemistry, Synthetic Organic Chemistry, Drug Design and Drug Development, CADD (Computer Aided Drug Design), Bioorganic and Medicinal Chemistry, Pharmacology and toxicology, BioInorganic Chemistry, Organometallic Chemistry, Radiopharmaceuticals, Chemical Biology, Anticancer agents in Medicinal Chemistry, Pharmaceutical Industry, Clinical Pharmacology, Pharmaceutical Sciences, Bioisostere, Analytical Chemistry, Nanomedicine, Stereochemistry, Pharmacovigilance,
May 24-26, 2018 Vienna, Austria Key Topics : Nutrition, Obesity and Diabetes, Public Health Nutrition, Nutrition in Women and Postmenopausal diet, Nutrition and Cancer Prevention, Diabetes Nutrition, Nutrition and Cardiovascular Health, Probiotic Nutrition and Enteral nutrition, Nutritional Physiology and Food Biochemistry, Nutritional Disorders and Treatment, Pediatric Nutrition and Obesity, Foods and Nutritional Supplements, Research in Nutrition and Food sciences, Sports Nutrition, Role of Nutrition in Disease Prevention, Malnutrition, Balanced Diet- Measures and Recommendations, Parenteral Nutrition, Nutrition in Chronic illness, Dental Nutrition and Weight Management, Animal & Plant Nutrition,
This collection discusses various micro/nanodevice design and fabrication for single-biomolecules detection. It will be an ideal reference text for graduate students and professionals in diverse subject areas including materials science, biomedical engineering, chemical engineering, mechanical engineering, and nanoscience. This book- Discusses techniques of single-biomolecule detection, their advantages, limitations, and applications. Covers comprehensively several electrochemical detection techniques. Provides single-molecule separation, sensing, imaging, sequencing, and analysis in detail. Examines different types of cantilever-based biomolecule sensing, and its limitations. Single Biomolecule Detection and Analysis covers single-biomolecule detection and characterization using micro/nanotechnologies and micro/nanofluidic devices, electrical and magnetic detection technologies, microscopy and spectroscopy techniques, single biomolecule optical, and nanopore devices. The text covers key important biosensors-based detection, stochastic optical reconstruction microscopy-based detection, electrochemical detection, metabolic engineering of animal cells, single-molecule intracellular delivery and tracking, terahertz spectroscopy-based detection, total internal reflection fluorescence (TIFR) detection, and Fluorescence Correlation Spectroscopy (FCS) detection. The text will be useful for graduate students and professionals in diverse subject areas including materials science, biomedical engineering, chemical engineering, mechanical engineering, and nanoscience. Discussing chemical process, physical process, separation, sensing, imaging, sequencing, and analysis of single-molecule detection, this text will be useful for graduate students and professionals in diverse subject areas including materials science, biomedical engineering, chemical engineering, mechanical engineering, and nanoscience. It covers microscopy and spectroscopy techniques for single-biomolecule detection, analysis, and their biomedical engineering applications.
Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.