تحسين النتائح
ترتيب حسب
من
الى
الصفحة 1
الصفحة 1
AI in clinical practice : A guide to artificial intelligence and digital medicine
Explains how artificial intelligence is applied to medicine, illustrating not only its enormous potential but also ancillary issues and the limits and risks inherent in its use on a large scale. The book focuses on the intersection between medicine and AI and its implications on the impact of human health care delivery. Topics discussed include wearable devices, health data, Internet of Things, virtual reality, robotic assistance system, and digital intelligence in the health sector. Additionally, sections discuss diagnostics and decision-making systems and machine/deep learning in clinical setting.
CADD and informatics in drug discovery
Updates knowledge on recent advances in computational and bioinformatics tools/techniques and their practical applications in modern drug design and discovery programme. Also it encompasses fundamental principles, advanced methodologies and applications of various CADD approaches including several cutting-edge areas / presenting recent developments covering ongoing trends in the field of computer-aided drug discovery. Having contributions by a global team of experts, the book is expected to be an ideal resource for drug discovery scientists, medicinal chemists, pharmacologists, toxicologists, phytochemists, biochemists, biologists, RandD personnel, researchers, students, teachers and those working in the field of drug discovery. It will fill the knowledge gaps that exist in the current CADD approaches and methodologies/ protocols being widely used in both academic and research practices. Further, a special focus on current status of various computational drug design approaches (SBDD, LBDD, De-novo drug design, Pharmacophore-based search), bioinformatics tools and databases, computational screening and modeling of phytochemicals/natural products, artificial intelligence and machine learning, and network pharmacology and system biology would certainly guide researchers, students or readers to conduct their research in the emerging area(s) of interest. It is also expected to be highly beneficial to different stakeholders working in the pharmaceutical and biotechnology industries (RandD), the academic as well as research sectors. .
Artificial intelligence and legal analytics : new tools for law practice in the digital age
The field of artificial intelligence (AI) and the law is on the cusp of a revolution. This book - designed to explain computational processes to non-programmers - describes how text analytic programs will change the practice of law, specifically by connecting computational models of legal reasoning directly with legal text.
Advancements in cybercrime investigation and digital forensics
Offers a comprehensive study on Advancements in Cybercrime Investigation and Digital Forensics, highlighting the most up-to-date tools that help to mitigate cyber-attacks and that extract digital evidence for forensic investigations to recover lost, purposefully deleted, or damaged files Vast manpower and resources are needed to investigate cybercrimes
JavaScript data structures and algorithms : An Introduction to understanding and implementing core data structure and algorithm fundamentals
Combines clear explanations of data structure and algorithm theory with practical code samples, examples and exercises, all specifically relevant to JavaScript Provides background information on object-oriented programming and native JavaScript concepts to help understand how everything fits together Illustrates how these theoretical computer science concepts ties back to practical applications in software engineering
Beyond the Worst-Case Analysis of Algorithms
There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.
Beginning Java Data Structures and Algorithms : Sharpen your problem solving skills by learning core computer science concepts in a pain-free manner
Teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and big O notation, later explains bubble, merge, quicksort, and other popular programming patterns. You’ll also learn about data structures such as binary trees, hash tables, and graphs. The book progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the book, you will know how to correctly implement common algorithms and data structures within your applications.
Anomaly Detection : Techniques and Applications
When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data.
Algorithmes dapproximation
Le champ des algorithmes d'approximation est aujourd'hui l'un des domaines de recherche les plus actifs en informatique. Il allie la profondeur de la théorie mathématique aux promesses d'applications pratiques d'un intérêt considérable. La plupart des problèmes issus d'applications relevant de domaines aussi différents que la conception de circuits VLSI, la conception et la planification de réseaux, l'ordonnancement, la théorie des jeux, la biologie ou la théorie des nombres, sont des problèmes NP-difficiles. Leur résolution exacte demanderait des ressources informatiques inaccessibles et ne peut donc être envisagée. Pour faire face à cette situation, un grand nombre d'algorithmes proposant des solutions approchées à ces problèmes ont été développés.
Matematica generale con il calcolatore
By introducing mathematical objects, it teaches students how to use a computer to perform numerical and symbolic calculations, define a function and calculate its values, plot and explore graphs, and execute simple algorithms. The course is rich in examples, applications, and models, drawn from economics, physics, biology, statistics, and mathematics itself. The analysis of these models constitutes, in a certain sense, the true purpose of the mathematical theory covered. Automatic calculation tools (mathematics software, spreadsheets) are used extensively to explore and illustrate concepts and properties. Mathcad® software, in particular, was used, both as a calculation tool and as a simple yet powerful programming language. Considerable space is devoted to approximation, emphasizing the distinction between numerical and symbolic calculation; to algorithms as a synthesis of the syntactic and semantic aspects of mathematical objects; and to computer simulation, interpreted as a "physical" experiment and a source of conjecture. The ability to use a calculator marks a sort of "democratization" of mathematics: even complex results, which have always required a broad background of knowledge and laborious calculations, are now quickly accessible to anyone who understands the meaning of mathematical objects and knows how to use the syntax.
Bio-informatique moléculaire : Une approche algorithmique = Molecular bioinformatics : An algorithmic approach
Deals with genetic maps, from the problem of sequence comparison and alignment, including DNA chips and genomic rearrangement. It thus covers a wide variety of topics relating to algorithmic and combinatorial processing of questions arising from molecular bioinformatics and biotechnology.
