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Practice questions in Psychopharmacology
An excellent addition to current resources in psychopharmacology for graduate and postgraduate trainees in psychiatry, neurology, medicine, pharmacy and pharmacology. A comprehensive series of relevant questions and an extensive bibliography that will be both a useful test of trainees’ progress and also a useful aide memoire and primer. Consists of 2600 questions in the form of ‘True/False Individual Statements, Extended Matching Items and Best of Five’ formats, organised in 52 papers in two volumes
The Medical Register
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Annual Report
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Practice Questions in Psychopharmacology
An excellent addition to current resources in psychopharmacology for graduate and postgraduate trainees in psychiatry, neurology, medicine, pharmacy and pharmacology. A comprehensive series of relevant questions and an extensive bibliography that will be both a useful test of trainees’ progress and also a useful aide memoire and primer. Consists of 2600 questions in the form of ‘True/False Individual Statements, Extended Matching Items and Best of Five’ formats, organised in 52 papers in two volumes
Machine Intelligence and Soft Computing
This book gathers selected papers presented at the International Conference on Machine Intelligence and Soft Computing (ICMISC 2020), held jointly by Vignan’s Institute of Information Technology, Visakhapatnam, India and VFSTR Deemed to be University, Guntur, AP, India during 03-04 September 2020. Topics covered in the book include the artificial neural networks and fuzzy logic, cloud computing, evolutionary algorithms and computation, machine learning, metaheuristics and swarm intelligence, neuro-fuzzy system, soft computing and decision support systems, soft computing applications in actuarial science, soft computing for database deadlock resolution, soft computing methods in engineering, and support vector machine.
Ecological Genomics
Researchers in the field of ecological genomics aim to determine how a genome or a population of genomes interacts with its environment across ecological and evolutionary timescales. Ecological genomics is trans-disciplinary by nature. Ecologists have turned to genomics to be able to elucidate the mechanistic bases of the biodiversity their research tries to understand. Genomicists have turned to ecology in order to better explain the functional cellular and molecular variation they observed in their model organisms. We provide an advanced-level book that covers this recent research and proposes future development for this field. A synthesis of the field of ecological genomics emerges from t...
Informatics in Control, Automation and Robotics
The present book includes a set of selected papers from the eighth "International Conference on Informatics in Control Automation and Robotics" (ICINCO 2011), held in Noordwijkerhout, The Netherlands, from 28 to 31 July 2011. The conference was organized in four simultaneous tracks: "Intelligent Control Systems and Optimization", "Robotics and Automation", "Signal Processing, Sensors, Systems Modeling and Control" and "Industrial Engineering, Production and Management". The book is based on the same structure. ICINCO received 322 paper submissions, not including those of workshops or special sessions, from 52 countries, in all continents. After a double blind paper review performed by the Pr...
Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems
The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users' requirements and the quality of solving targeted problems in domain applications. Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems surveys, analyzes, and compares the most effective algorithms for mining all kinds of logical rules. Global academics and professionals in related fields have come together to create this unique knowledge-sharing resources which will serve as a forum for future collaborations.
Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning
By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.
