Augmented Intelligence is the intersection of machine learning and advanced applications, where clinical knowledge and medical data converge on a single platform. The potential benefits of Augmented Intelligence are realized when it is used in the context of workflows and systems that healthcare practitioners operate and interact with. Unlike Artificial Intelligence, which tries to replicate human intelligence, Augmented Intelligence works with and amplifies human intelligence[103 - Augmented Intelligence [Электронный ресурс] https://gartner.com URL: https://www.gartner.com/en/information-technology/glossary/augmented-intelligence#:~: text=Augmented% 20intelligence%20is%20a%20design, decision%20making%20and%20new%20experiences (дата обращения: 28.01.2022)].
Augmented reality (AR) is an interactive experience of a real-world environment where the objects that reside in the real-world are «augmented» by computer-generated perceptual information, sometimes across multiple sensory modalities, including visual, auditory, haptic, somatosensory, and olfactory[104 - Augmented reality [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Augmented_reality (дата обращения: 09.04.2023)].
Augmented reality technologies are visualization technologies based on adding information or visual effects to the physical world by overlaying graphic and/or sound content to improve user experience and interactive features[105 - Технологии дополненной реальности [Электронный ресурс] https://dzen.ru URL: https://dzen.ru/a/Y_yfdHIFHgahdc-6 (дата обращения 04.07.2023)].
Auto Associative Memory is a single layer neural network in which the input training vector and the output target vectors are the same. The weights are determined so that the network stores a set of patterns. As shown in the following figure, the architecture of Auto Associative memory network has «n’ number of input training vectors and similar «n’ number of output target vectors[106 - Auto Associative Memory [Электронный ресурс] www.tutorialspoint.com URL: https://www.tutorialspoint.com/artificial_neural_network/artificial_neural_network_associate_memory.htm#:~:text= These%20kinds%20of%20neural%20networks, with%20the%20given%20input%20pattern (дата обращения: 07.07.2022)].
Autoencoder (AE) is a type of Artificial Neural Network used to produce efficient representations of data in an unsupervised and non-linear manner, typically to reduce dimensionality[107 - Autoencoder [Электронный ресурс] https://neurohive.io URL: https://neurohive.io/ru/osnovy-data-science/avtojenkoder-tipy-arhitektur-i-primenenie/ (дата обращения: 28.01.2022)].
Automata theory – the study of abstract machines and automata, as well as the computational problems that can be solved using them. It is a theory in theoretical computer science and discrete mathematics (a subject of study in both mathematics and computer science). Automata theory (part of the theory of computation) is a theoretical branch of Computer Science and Mathematics, which mainly deals with the logic of computation with respect to simple machines, referred to as automata[108 - Automata theory [Электронный ресурс] https://vvsu.ru URL: https://www.vvsu.ru/files/529128A0-237E-434E-8B31-4553FB108EF2.ppt (дата обращения: 28.01.2022)],[109 - Automata theory [Электронный ресурс] www.geeksforgeeks.org URL: https://www.geeksforgeeks.org/introduction-of-theory-of-computation/ (дата обращения: 07.07.2022)].
Automated control system – a set of software and hardware designed to control technological and (or) production equipment (executive devices) and the processes they produce, as well as to control such equipment and processes[110 - Автоматизированная система управления [Электронный ресурс] https://safe-surf.ru URL: https://safe-surf.ru/glossary/ru/599613 (дата обращения: 24.03.2023)].
Automated planning and scheduling (also simply AI planning) is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are complex and must be discovered and optimized in multidimensional space. Planning is also related to decision theory[111 - Automated planning and scheduling [Электронный ресурс] https://researcher.watson.ibm.com URL: https://researcher.watson.ibm.com/researcher/view_group.php?id=8432 (дата обращения: 28.01.2022)].
Automated processing of personal data – processing of personal data using computer technology[112 - Автоматизированная обработка персональных данных [Электронный ресурс] URL: https://10.rkn.gov.ru/docs/10/Pravila_obrabotki_PD.pdf (дата обращения: 24.03.2023)].
Automated reasoning is an area of computer science and mathematical logic dedicated to understanding different aspects of reasoning. The study of automated reasoning helps produce computer programs that allow computers to reason completely, or nearly completely, automatically. Although automated reasoning is considered a sub-field of artificial intelligence, it also has connections with theoretical computer science, and even philosophy[113 - Automated reasoning [Электронный ресурс] https://techtarget.com URL: https://www.techtarget.com/searchenterpriseai/definition/automated-reasoning (дата обращения: 18.02.2022)].
Automated system is an organizational and technical system that guarantees the development of solutions based on the automation of information processes in various fields of activity[114 - Автоматизированная система [Электронный ресурс] https://prezi.com URL: https://prezi.com/p/kjuyqjgiuaux/presentation/ (дата обращения: 24.03.2023)].
Automation bias is when a human decision maker favors recommendations made by an automated decision-making system over information made without automation, even when the automated decision-making system makes errors[115 - Automation bias [Электронный ресурс] https://databricks.com URL: https://databricks.com/glossary/automation-bias#:~:text=Automation%20bias %20is%20an%20over, aids%20and%20decision %20support%20systems.&text= It%20is%20a%20human %20tendency, leaning %20towards%20%22automation%20bias%22 (дата обращения: 26.01.2022)].
Automation is a technology by which a process or procedure is performed with minimal human intervention[116 - Automation [Электронный ресурс] https://tis-eg.com URL: https://tis-eg.com/en/what-is-automation-mean/ (дата обращения: 24.03.2023)].
Autonomic computing is the ability of a system to adaptively self-manage its own resources for high-level computing functions without user input[117 - Autonomic computing [Электронный ресурс] https://www.accenture.com URL: https://www.accenture.com/us-en/insights/applied-intelligence/artificial-intelligence-glossary (дата обращения: 26.03.2023)].
Autonomous artificial intelligence is a biologically inspired system that tries to reproduce the structure of the brain, the principles of its operation with all the properties that follow from this[118 - Autonomous artificial intelligence [Электронный ресурс] https://books.google.ru URL: https://books.google.ru/books?id=_R5XEAAAQBAJ&pg=PT217&lpg=PT217&dq=Autonomous +artificial +intelligence+a+biologically+inspired+ system+that+tries+to+reproduce+ the+structure+of+ the+brain&source= bl&ots=NKsVUXEkc6&sig= ACfU3U23DpeuDH11ONr GFufhEpuVkLGsCw&hl =ru&sa=X&ved= 2ahUKEwiz0bqhnPn9Ah UCt4sKHQ5RCDoQ6AF6BAgvEAM#v =onepage&q=Autonomous %20artificial%20intelligence% 20a%20biologically%20inspired %20system%20that%20tries %20to%20reproduce% 20the%20structure %20of%20the%20brain&f=false (дата обращения: 26.03.2023)],[119 - Автономный искусственный интеллект https://stepik.org URL: https://stepik.org/lesson/292708/step/2 (дата обращения: 26.03.2023)].
Autonomous car (also self-driving car, robot car, and driverless car) is a vehicle that is capable of sensing its environment and moving with little or no human input[120 - Autonomous car [Электронный ресурс] https://synopsys.com URL: https://www.synopsys.com/automotive/what-is-autonomous-car.html (дата обращения: 28.01.2022)].
Autonomous is a machine is described as autonomous if it can perform its task or tasks without needing human intervention[121 - Autonomous [Электронный ресурс] https://www.telusinternational.com URL: https://www.telusinternational.com/insights/ai-data/article/50-beginner-ai-terms-you-should-know (дата обращения: 26.03.2023)].
Autonomous robot is a robot that performs behaviors or tasks with a high degree of autonomy. Autonomous robotics is usually considered to be a subfield of artificial intelligence, robotics, and information engineering[122 - Autonomous robot [Электронный ресурс] https://techopedia.com URL: https://www.techopedia.com/definition/32694/autonomous-robot (дата обращения: 28.01.2022)].
Autonomous vehicle is a mode of transport based on an autonomous driving system. The control of an autonomous vehicle is fully automated and carried out without a driver using optical sensors, radar and computer algorithms[123 - Автономное транспортное средство [Электронный ресурс] https://ru.wikipedia.org URL: https://ru.wikipedia.org/wiki/Автономный_транспорт (дата обращения: 24.03.2023)].
Autoregressive Model is an autoregressive model is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step. In statistics and signal processing, an autoregressive model is a representation of a type of random process. It is used to describe certain time-varying processes in nature, economics, etc.[124 - Autoregressive Model [Электронный ресурс] https://wiki.loginom.ru URL: https://wiki.loginom.ru/articles/autoregressive-model.html (дата обращения: 08.02.2022)].
Auxiliary intelligence – systems based on artificial intelligence that complement human decisions and are able to learn in the process of interacting with people and the environment.
Average precision is a metric for summarizing the performance of a ranked sequence of results. Average precision is calculated by taking the average of the precision values for each relevant result (each result in the ranked list where the recall increases relative to the previous result)[125 - Average precision [Электронный ресурс] https://jonathan-hui.medium.com URL: https://jonathan-hui.medium.com/map-mean-average-precision-for-object-detection-45c121a31173 (дата обращения: 28.01.2022)].
Ayasdi is an enterprise scale machine intelligence platform that delivers the automation that is needed to gain competitive advantage from the company’s big and complex data. Ayasdi supports large numbers of business analysts, data scientists, endusers, developers and operational systems across the organization, simultaneously creating, validating, using and deploying sophisticated analyses and mathematical models at scale[126 - Ayasdi [Электронный ресурс] https://www.predictiveanalyticstoday.com URL: https://www.predictiveanalyticstoday.com/ayasdi/ (дата обращения: 20.06.2023)].
«B»
Backpropagation through time (BPTT) is a gradient-based technique for training certain types of recurrent neural networks. It can be used to train Elman networks. The algorithm was independently derived by numerous researchers[127 - Backpropagation through time [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Backpropagation_through_time (дата обращения: 11.05.2023)].
Backpropagation, also called «backward propagation of errors,» is an approach that is commonly used in the training process of the deep neural network to reduce errors[128 - Backpropagation [Электронный ресурс] https://www.guru99.com URL: https://www.guru99.com/backpropogation-neural-network.html (дата обращения: 11.05.2023)].
Backward Chaining, also called goal-driven inference technique, is an inference approach that reasons backward from the goal to the conditions used to get the goal. Backward chaining inference is applied in many different fields, including game theory, automated theorem proving, and artificial intelligence[129 - Backward Chaining [Электронный ресурс] www.educba.com URL: https://www.educba.com/backward-chaining (дата обращения 11.03.2022)].
Bag-of-words model in computer vision. In computer vision, the bag-of-words model (BoW model) can be applied to image classification, by treating image features as words. In document classification, a bag of words is a sparse vector of occurrence counts of words; that is, a sparse histogram over the vocabulary. In computer vision, a bag of visual words is a vector of occurrence counts of a vocabulary of local image features[130 - Bag-of-words model in computer vision [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Bag-of-words_model_in_computer_vision (дата обращения: 10.05.2023)].
Bag-of-words model is a simplifying representation used in natural language processing and information retrieval (IR). In this model, a text (such as a sentence or a document) is represented as the bag (multiset) of its words, disregarding grammar and even word order but keeping multiplicity. The bag-of-words model has also been used for computer vision. The bag-of-words model is commonly used in methods of document classification where the (frequency of) occurrence of each word is used as a feature for training a classifier[131 - Bag-of-words model [Электронный ресурс] https://machinelearningmastery.ru URL: https://www.machinelearningmastery.ru/gentle-introduction-bag-words-model/ (дата обращения: 11.03.2022)].
Baldwin effect – the skills acquired by organisms during their life as a result of learning, after a certain number of generations, are recorded in the genome[132 - Эффект Балдвина [Электронный ресурс] https://apr.moscow URL: https://apr.moscow/content/data/6/11 Технологии искусственного интеллекта. pdf (дата обращения: 11.07.2023)].
Baseline is a model used as a reference point for comparing how well another model (typically, a more complex one) is performing. For example, a logistic regression model might serve as a good baseline for a deep model. For a particular problem, the baseline helps model developers quantify the minimal expected performance that a new model must achieve for the new model to be useful[133 - Baseline [Электронный ресурс] https://developers.google.com URL: https://developers.google.com/machine-learning/glossary#baseline (дата обращения: 28.03.2023)].
Batch – the set of examples used in one gradient update of model training[134 - Batch [Электронный ресурс] https://www.primeclasses.in URL: https://www.primeclasses.in/glossary/data-science-course/machine-learning/batch (дата обращения: 20.06.2023)].
Batch Normalization is a preprocessing step where the data are centered around zero, and often the standard deviation is set to unity[135 - Batch Normalization [Электронный ресурс] https://books.google.ru URL: https://books.google.ru/books?id=Batch Normalization (дата обращения: 20.06.2023)].
Batch size – the number of examples in a batch. For example, the batch size of SGD is 1, while the batch size of a mini-batch is usually between 10 and 1000. Batch size is usually fixed during training and inference; however, TensorFlow does permit dynamic batch sizes[136 - Batch size [Электронный ресурс] https://www.gabormelli.com URL: https://www.gabormelli.com/RKB/Batch_Size (дата обращения: 29.06.2023)],[137 - Batch size [Электронный ресурс] https://developers.google.com URL: https://developers.google.com/machine-learning/glossary#batch-size (дата обращения: 29.06.2023)].
Bayes’s Theorem is a famous theorem used by statisticians to describe the probability of an event based on prior knowledge of conditions that might be related to an occurrence[138 - Теорема Байеса [Электронный ресурс] https://habr.com URL: https://habr.com/ru/articles/598979/ (дата обращения: 03.07.2023)].
Bayesian classifier in machine learning is a family of simple probabilistic classifiers based on the use of the Bayes theorem and the «naive» assumption of the independence of the features of the objects being classified[139 - Байесовский классификатор в машинном обучении [Электронный ресурс] https://wiki.loginom.ru URL: https://wiki.loginom.ru/articles/bayesian_classifier.html (дата обращения: 07.07.2022)].
Bayesian Filter is a program using Bayesian logic. It is used to evaluate the header and content of email messages and determine whether or not it constitutes spam – unsolicited email or the electronic equivalent of hard copy bulk mail or junk mail. A Bayesian filter works with probabilities of specific words appearing in the header or content of an email. Certain words indicate a high probability that the email is spam, such as Viagra and refinance[140 - Bayesian Filter [Электронный ресурс] https://certsrv.ru URL: http://certsrv.ru/eset_ss.ru/pages/bayes_filter.htm (дата обращения: 12.02.2022)].
Bayesian Network, also called Bayes Network, belief network, or probabilistic directed acyclic graphical model, is a probabilistic graphical model (a statistical model) that represents a set of variables and their conditional dependencies via a directed acyclic graph[141 - Bayesian Network [Электронный ресурс] https://dic.academic.ru URL: https://dic.academic.ru/dic.nsf/ruwiki/1738444 (дата обращения: 31.01.2022)].
Bayesian optimization is a probabilistic regression model technique for optimizing computationally expensive objective functions by instead optimizing a surrogate that quantifies the uncertainty via a Bayesian learning technique. Since Bayesian optimization is itself very expensive, it is usually used to optimize expensive-to-evaluate tasks that have a small number of parameters, such as selecting hyperparameters[142 - Bayesian optimization [Электронный ресурс] https://developers.google.com URL: https://developers.google.com/machine-learning/glossary#bayesian-optimization (дата обращения: 28.03.2023)].
Bayesian programming is a formalism and a methodology for having a technique to specify probabilistic models and solve problems when less than the necessary information is available[143 - Bayesian programming [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Bayesian_programming (дата обращения: 28.03.2023)],[144 - Байесовское программирование [Электронный ресурс] https://ru.wikipedia.org URL: https://ru.wikipedia.org/wiki/Байесовское_программирование (дата обращения: 28.03.2023)].
Bees’ algorithm is a population-based search algorithm which was developed by Pham, Ghanbarzadeh and et al. in 2005. It mimics the food foraging behaviour of honey bee colonies. In its basic version the algorithm performs a kind of neighbourhood search combined with global search, and can be used for both combinatorial optimization and continuous optimization. The only condition for the application of the bee’s algorithm is that some measure of distance between the solutions is defined. The effectiveness and specific abilities of the bee’s algorithm have been proven in a number of studies[145 - Bees algorithm [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Bees_algorithm#cite_note-Pham_&_al,_2005-1 (дата обращения: 27.03.2023)].
Behavior informatics (BI) — the informatics of behaviors so as to obtain behavior intelligence and behavior insights[146 - Behavior informatics (BI) [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Behavior_informatics (дата обращения: 01.05.2023)].
Behavior tree (BT) is a mathematical model of plan execution used in computer science, robotics, control systems and video games. They describe switchings between a finite set of tasks in a modular fashion. Their strength comes from their ability to create very complex tasks composed of simple tasks, without worrying how the simple tasks are implemented. BTs present some similarities to hierarchical state machines with the key difference that the main building block of a behavior is a task rather than a state. Its ease of human understanding makes BTs less error-prone and very popular in the game developer community. BTs have shown to generalize several other control architectures[147 - Behavior tree (BT) [Электронный ресурс] https://habr.com URL: https://habr.com/ru/company/cloud_mts/blog/306214/ (дата обращения: 31.01.2022)].
Belief-desire-intention software model (BDI) is a software model developed for programming intelligent agents. Superficially characterized by the implementation of an agent’s beliefs, desires and intentions, it actually uses these concepts to solve a particular problem in agent programming. In essence, it provides a mechanism for separating the activity of selecting a plan (from a plan library or an external planner application) from the execution of currently active plans. Consequently, BDI agents are able to balance the time spent on deliberating about plans (choosing what to do) and executing those plans (doing it). A third activity, creating the plans in the first place (planning), is not within the scope of the model, and is left to the system designer and programmer[148 - Belief-desire-intention software model (BDI) [Электронный ресурс] https://fccland.ru URL: https://fccland.ru/stati/22848-model-ubezhdeniy-zhelaniy-i-namereniy.html (дата обращения: 31.01.2022)].
Bellman equation – named after Richard E. Bellman, is a necessary condition for optimality associated with the mathematical optimization method known as dynamic programming. It writes the «value» of a decision problem at a certain point in time in terms of the payoff from some initial choices and the «value» of the remaining decision problem that results from those initial choices. This breaks a dynamic optimization problem into a sequence of simpler subproblems, as Bellman’s «principle of optimality» prescribes[149 - Bellman equation [Электронный ресурс] https://mruanova.medium.com URL: https://mruanova.medium.com/bellman-equation-90f2f0deaa88 (дата обращения 28.02.2022)].
Benchmark (also benchmark program, benchmarking program, benchmark test) – test program or package for evaluating (measuring and/or comparing) various aspects of the performance of a processor, individual devices, computer, system or a specific application, software; a benchmark that allows products from different manufacturers to be compared against each other or against some standard. For example, online benchmark – online benchmark; standard benchmark – standard benchmark; benchmark time comparison – comparison of benchmark execution times[150 - Benchmark [Электронный ресурс] https://medium.com URL: https://medium.com/@tauheedul/it-hardware-benchmarks-for-machine-learning-and-artificial-intelligence-6183ceed39b8 (дата обращения 11.03.2022)].
Benchmarking is a set of techniques that allow you to study the experience of competitors and implement best practices in your company[151 - Бенчмаркинг [Электронный ресурс] https://trends.rbc.ru URL: https://trends.rbc.ru/trends/education/61540f1e9a7947ed382de149 (дата обращения: 28.03.2023)].
BETA refers to a phase in online service development in which the service is coming together functionality-wise but genuine user experiences are required before the service can be finished in a user-centered way. In online service development, the aim of the beta phase is to recognize both programming issues and usability-enhancing procedures. The beta phase is particularly often used in connection with online services and it can be either freely available (open beta) or restricted to a specific target group (closed beta)[152 - BETA [Электронный ресурс] www.sofokus.com URL: https://www.sofokus.com/glossary-of-digital-business/#ABCD (дата обращения: 07.07.2022)].
Bias is a systematic trend that causes differences between results and facts. Error exists in the numbers of the data analysis process, including the source of the data, the estimate chosen, and how the data is analyzed. Error can seriously affect the results, for example, when studying people’s shopping habits. If the sample size is not large enough, the results may not reflect the buying habits of all people. That is, there may be discrepancies between survey results and actual results[153 - Bias [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Bias_(statistics) (дата обращения: 26.06.2023)].
Biased algorithm – systematic and repetitive errors in a computer system that lead to unfair results, such as one privilege persecuting groups of users over others. Also, sexist and racist algorithms[154 - Biased algorithm [Электронный ресурс] https://en.wikipedia.org URL: https://en.wikipedia.org/wiki/Algorithmic_bias (дата обращения: 27.03.2023)],[155 - Алгоритмическая предвзятость [Электронный ресурс] https://ru.wikibrief.org URL: https://ru.wikibrief.org/wiki/Algorithmic_bias (дата обращения: 27.03.2023)].
