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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.
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
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.
Improving and Accelerating Therapeutic Development for Nervous System Disorders is the summary of a workshop convened by the IOM Forum on Neuroscience and Nervous System Disorders to examine opportunities to accelerate early phases of drug development for nervous system drug discovery. Workshop participants discussed challenges in neuroscience research for enabling faster entry of potential treatments into first-in-human trials, explored how new and emerging tools and technologies may improve the efficiency of research, and considered mechanisms to facilitate a more effective and efficient development pipeline. There are several challenges to the current drug development pipeline for nervous system disorders. The fundamental etiology and pathophysiology of many nervous system disorders are unknown and the brain is inaccessible to study, making it difficult to develop accurate models. Patient heterogeneity is high, disease pathology can occur years to decades before becoming clinically apparent, and diagnostic and treatment biomarkers are lacking. In addition, the lack of validated targets, limitations related to the predictive validity of animal models - the extent to which the model predicts clinical efficacy - and regulatory barriers can also impede translation and drug development for nervous system disorders. Improving and Accelerating Therapeutic Development for Nervous System Disorders identifies avenues for moving directly from cellular models to human trials, minimizing the need for animal models to test efficacy, and discusses the potential benefits and risks of such an approach. This report is a timely discussion of opportunities to improve early drug development with a focus toward preclinical trials.
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 21-22,2018 Vienna, Austria Key Topics : Reproductive Health, Gynecology and obstetrics, Pregnancy, Women Health, Menopause, Reproductive Toxicology, Reproductive Medicine, Urologic and Gynecologic Disorders, Reproductive Endocrinology and Infertility, Women Reproductive Cancers, Reproductive Technology, Sexually Transmitted Diseases, Lifestyle Factors and Reproductive Health, Maternal and Child Health, Abortions and women’s health, Family Planning, Women Health Nursing, Effects of Obesity on Women’s Health and Pregnancy:, Breast Cancer during Pregnancy, Reproductive Hazards for Female Workers,