Psychopharmacology Algorithms


Book Description

Algorithms serve an important purpose in the field of psychopharmacology as heuristics for avoiding the biases and cognitive lapses that are common when prescribing for many conditions whose treatment is based on complex data. Unique in the field, this title compiles twelve papers from the Psychopharmacology Algorithm Project at the Harvard South Shore Psychiatry Residency Training Program and presents practical ways to adopt evidence-based practices into the day-to-day treatment of patients. Psychopharmacology Algorithms is a useful resource for practicing psychiatrists, residents, and fellows, as well as psychiatric nurse practitioners, psychiatric physician assistants who prescribe, advanced practice pharmacists who prescribe, and primary care clinicians. Teachers of psychopharmacology may find it particularly valuable. Researchers in clinical psychopharmacology may find it helpful in identifying important practice areas that are in need of further study.




Algorithms of Anxiety


Book Description

Machine learning algorithms are widely presumed to herald a world in which the crippling burdens of anxiety can be left behind. The digital revolution promises a brave new world where individuals, communities and organizations can at last take control of the future – anticipating, designing and commanding the future, possibly even with mathematical exactitude. Yet, paradoxically, algorithms have unleashed widespread fears and forebodings about the impact of digital technologies. Whether it’s worries about unemployment, distress about social media’s harmful effects on teenagers, or the fear of intrusive digital surveillance, we live in an age of turbo-charged anxiety where the prophecies of algorithms are increasingly enmeshed with fundamental disruption and anxieties about the future. In this book, Anthony Elliott examines how machine learning algorithms are not only transforming global institutions but also rewriting our personal lives. He tells this story through a wide-ranging analysis which takes in ChatGPT, Amazon, the Metaverse, Martin Ford, Netflix, Uber, Bernard Stiegler, Squid Game, Kate Crawford, LaMDA, Byung-Chul Han, autonomous drones, Jean Baudrillard and the automation of warfare. Questioning why people often assume that they need to adopt new technologies in order to lead fulfilling lives, Elliott argues that people may be as much entranced as inspired by their outsourcing of personal decision-making to smart machines.




Psychiatry Algorithms for Primary Care


Book Description

Psychiatry Algorithms for Primary Care is a practical, quick reference guide to psychiatric assessment and mental healthcare in general practice. Providing algorithms informed by evidence-based guidelines, this easy-to-use resource helps busy medical and healthcare professionals quickly assess mental health problems, make informed treatment decisions, and understand when referrals to specialist mental health services are appropriate. Drawing from their extensive experience in general practice and psychiatry, the authors provide clear and authoritative guidance on a wide range of common psychiatric disorders, complex scenarios, and special considerations. Unique visual management algorithms define assessment, diagnosis, investigations and management for each condition, including Bipolar Affective Disorder, Psychosis, Depression, Dementia, and Attention Deficit Hyperactivity Disorder. Up-to-date information on medication choices and counselling strategies is found throughout the text. Designed for informing swift clinical decisions in demanding primary care settings, this indispensable reference guide: Conforms to the diagnostic criteria in the current edition of the World Health Organization’s International Classification of Diseases Contains algorithms informed by the Royal College of General Practitioners (RCGP), Royal College of Psychiatrists (RCPsych), and the National Institute for Health and Care Excellence (NICE) guidelines Explores common complaints that can suggest psychological or psychiatric disorders, such as insomnia and fatigue Outlines special mental health considerations related to children, intellectual disability, autism, the elderly, and pregnancy Includes appendices covering commonly prescribed drugs and physical examinations for patients with severe mental illness Features numerous self-assessment questions and links to online reference tools for General Practitioners Psychiatry Algorithms for Primary Care is a much-needed resource for medical students and trainees, physicians and healthcare professionals in general practice, nurse practitioners, and practitioners in other fields such as urgent care and emergency medicine.




Designing the Mind: The Principles of Psychitecture


Book Description

The Instant Cult Classic on the Art of Reprogramming Your Own Psychological SoftwareA bold and fascinating dive into the nuts and bolts of psychological evolution, Designing the Mind: The Principles of Psychitecture is part philosophical manifesto, part practical self-development guide, all based on the teachings of legendary thinkers like Marcus Aurelius, Lao Tzu, Friedrich Nietzsche, and Abraham Maslow. The ideas and techniques it offers are all integrated into a vital theory for helping individuals scale the heights of self-mastery and lead great lives."A fascinating framework" - Scott Barry Kaufman, PhD, author of Transcend: The New Science of Self-ActualizationThis visionary guide argues that the mind can be compared to software, made up of many interwoven algorithms which were originally programmed by natural selection. Though most never learn to alter their default programming, it is possible to rewire cognitive biases, change ingrained habits, and transform emotional reactions. The process of psychitecture enables you to unplug from your own mind, identify its underlying patterns, and become the architect of your own enlightenment.




Common Mental Health Disorders


Book Description

Bringing together treatment and referral advice from existing guidelines, this text aims to improve access to services and recognition of common mental health disorders in adults and provide advice on the principles that need to be adopted to develop appropriate referral and local care pathways.




Love in the Time of Algorithms


Book Description

“If online dating can blunt the emotional pain of separation, if adults can afford to be increasingly demanding about what they want from a relationship, the effect of online dating seems positive. But what if it’s also the case that the prospect of finding an ever more compatible mate with the click of a mouse means a future of relationship instability, a paradox of choice that keeps us chasing the illusive bunny around the dating track?” It’s the mother of all search problems: how to find a spouse, a mate, a date. The escalating marriage age and declin­ing marriage rate mean we’re spending a greater portion of our lives unattached, searching for love well into our thirties and forties. It’s no wonder that a third of America’s 90 million singles are turning to dating Web sites. Once considered the realm of the lonely and desperate, sites like eHarmony, Match, OkCupid, and Plenty of Fish have been embraced by pretty much every demographic. Thanks to the increasingly efficient algorithms that power these sites, dating has been transformed from a daunting transaction based on scarcity to one in which the possibilities are almost endless. Now anyone—young, old, straight, gay, and even married—can search for exactly what they want, connect with more people, and get more information about those people than ever before. As journalist Dan Slater shows, online dating is changing society in more profound ways than we imagine. He explores how these new technologies, by altering our perception of what’s possible, are reconditioning our feelings about commitment and challenging the traditional paradigm of adult life. Like the sexual revolution of the 1960s and ’70s, the digital revolution is forcing us to ask new questions about what constitutes “normal”: Why should we settle for someone who falls short of our expectations if there are thousands of other options just a click away? Can commitment thrive in a world of unlimited choice? Can chemistry really be quantified by math geeks? As one of Slater’s subjects wonders, “What’s the etiquette here?” Blending history, psychology, and interviews with site creators and users, Slater takes readers behind the scenes of a fascinating business. Dating sites capitalize on our quest for love, but how do their creators’ ideas about profits, morality, and the nature of desire shape the virtual worlds they’ve created for us? Should we trust an industry whose revenue model benefits from our avoiding monogamy? Documenting the untold story of the online-dating industry’s rise from ignominy to ubiquity—beginning with its early days as “computer dating” at Harvard in 1965—Slater offers a lively, entertaining, and thought provoking account of how we have, for better and worse, embraced technology in the most intimate aspect of our lives.




Biomedical Data Mining for Information Retrieval


Book Description

BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.




Algorithms for Decision Making


Book Description

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.




Textbook of Treatment Algorithms in Psychopharmacology


Book Description

Psychopharmacology is the study of drugs used to treat psychiatric disorders. This textbook looks at the use of clinical algorithms in relation to clinical psychopharmacology, especially the nature and current use of algorithms, and their future potential for the medical community.