Learning Medicine

"Fantastic... I wish I had read your book before med school!" -Nathan Brajer, medical student "A great read and a great primer on how med students learn and think." -Jess Friedman, medical student and former teacher Succeeding at medical school is difficult under the best of circumstances, and poor study skills only make matters worse. This book offers a comprehensive, evidence-based methodology for learning medicine that will help you to take command of your medical school experience and become the best doctor you can be. With this book, you will: >Understand the science of learning and how to study most effectively > Learn how to control forgetting with spaced repetition > Get a guided tour of med school, with specific tips for how to learn each course subject

This book considers the evolution of medical education over the centuries, presents various theories and principles of learning (pedagogical and andragogical) and discusses different forms of medical curriculum and the strategies employed to develop them, citing examples from medical schools in developed and developing nations. Instructional methodologies and tools for assessment and evaluation are discussed at length and additional elements of modern medical teaching, such as writing skills, communication skills, evidence-based medicine, medical ethics, skill labs and webinars, are fully considered. In discussing these topics, the authors draw upon the personal experience that they have gained in learning, teaching and disseminating knowledge in many parts of the world over the past four decades. Medical Education in Modern Times will be of interest for medical students, doctors, teachers, nurses, paramedics and health and education planners.

This definitive careers guide gives a true insight into the meaning and process of becoming a doctor.

Machine Learning in Medicine covers the state-of-the-art techniques of machine learning and their applications in the medical field. It presents several computer-aided diagnosis (CAD) systems, which have played an important role in the diagnosis of several diseases in the past decade, e.g., cancer detection, resulting in the development of several successful systems. New developments in machine learning may make it possible in the near future to develop machines that are capable of completely performing tasks that currently cannot be completed without human aid, especially in the medical field. This book covers such machines, including convolutional neural networks (CNNs) with different activation functions for small- to medium-size biomedical datasets, detection of abnormal activities stemming from cognitive decline, thermal dose modelling for thermal ablative cancer treatments, dermatological machine learning clinical decision support systems, artificial intelligence-powered ultrasound for diagnosis, practical challenges with possible solutions for machine learning in medical imaging, epilepsy diagnosis from structural MRI, Alzheimer's disease diagnosis, classification of left ventricular hypertrophy, and intelligent medical language understanding. This book will help to advance scientific research within the broad field of machine learning in the medical field. It focuses on major trends and challenges in this area and presents work aimed at identifying new techniques and their use in biomedical analysis, including extensive references at the end of each chapter.

Learning Medicine is a must-read for anyone thinking of a career in medicine, or who is already in the training process and wants to understand and explore the various options and alternatives along the way. Whatever your background, whether you are school-leaver or mature student, if you are interested in finding out more about becoming and being a good doctor, this is the book for you. In continuous publication since 1983, and now in its eighteenth edition, Learning Medicine provides the most current, honest and informative source of essential knowledge combined with pragmatic guidance. Learning Medicine describes medical school courses, explains foundation years and outlines the wide range of speciality choices allowing tomorrow's doctors to decide about their future careers; but it also goes further to consider the privilege and responsibility of being a doctor, providing food for thought and reflection throughout a long and rewarding career.

As our nation enters a new era of medical science that offers the real prospect of personalized health care, we will be confronted by an increasingly complex array of health care options and decisions. The Learning Healthcare System considers how health care is structured to develop and to apply evidence-from health profession training and infrastructure development to advances in research methodology, patient engagement, payment schemes, and measurement-and highlights opportunities for the creation of a sustainable learning health care system that gets the right care to people when they need it and then captures the results for improvement. This book will be of primary interest to hospital and insurance industry administrators, health care providers, those who train and educate health workers, researchers, and policymakers. The Learning Healthcare System is the first in a series that will focus on issues important to improving the development and application of evidence in health care decision making. The Roundtable on Evidence-Based Medicine serves as a neutral venue for cooperative work among key stakeholders on several dimensions: to help transform the availability and use of the best evidence for the collaborative health care choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care; and, ultimately, to ensure innovation, quality, safety, and value in health care.

A path-breaking work at last available in paper, History, Medicine, and the Traditions of Renaissance Learning is Nancy G. Siraisi’s examination of the intersections of medically trained authors and history from 1450 to 1650. Rather than studying medicine and history as separate traditions, Siraisi calls attention to their mutual interaction in the rapidly changing world of Renaissance erudition. With remarkably detailed scholarship, Siraisi investigates doctors’ efforts to explore the legacies handed down to them from ancient medical and anatomical writings.