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This book focuses on a variety of interdisciplinary perspectives concerning the theory and application of artificial intelligence (AI) in medicine, medically oriented human biology, and healthcare. The list of topics includes the application of AI in biomedicine and clinical medicine, machine learning-based decision support, robotic surgery, data analytics and mining, laboratory information systems, and usage of AI in medical education. Special attention is given to the practical aspect of a study. Hence, the inclusion of a clinical assessment of the usefulness and potential impact of the submitted work is strongly highlighted.

Technology: general issues --- History of engineering & technology --- computational intelligence --- medical assistance --- instance-based learning --- healthcare --- clinical decision support systems --- deep neural networks --- medical imaging --- backdoor attacks --- security and privacy --- COVID-19 --- gastric cancer --- endoscopy --- deep learning --- convolutional neural network --- brain --- pituitary adenoma --- dysembryoplastic neuroepithelial tumor --- DNET --- ganglioglioma --- digital pathology --- computer vision --- machine learning --- CNN --- ATLAS --- HarDNet --- Swin transformer --- segmentation --- U-Net --- cerebral infarction --- CycleGAN --- advanced statistics --- schizophrenia --- aggression --- forensic psychiatry --- medical image segmentation --- CT image segmentation --- kernel density --- semi-automated labeling tool --- Bayesian learning --- neuroimaging --- feature selection --- kernel formulation --- mental disorders --- MRI --- visual acuity --- fundus images --- ophthalmology --- SVM

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How magicians exploit the natural functioning of our brains to astonish and amaze usHow do magicians make us see the impossible? The Illusionist Brain takes you on an unforgettable journey through the inner workings of the human mind, revealing how magicians achieve their spectacular and seemingly impossible effects by interfering with your cognitive processes. Along the way, this lively and informative book provides a guided tour of modern neuroscience, using magic as a lens for understanding the unconscious and automatic functioning of our brains.We construct reality from the information stored in our memories and received through our senses, and our brains are remarkably adept at tricking us into believing that our experience is continuous. In fact, our minds create our perception of reality by elaborating meanings and continuities from incomplete information, and while this strategy carries clear benefits for survival, it comes with blind spots that magicians know how to exploit. Jordi Camí and Luis Martínez explore the many different ways illusionists manipulate our attention—making us look but not see—and take advantage of our individual predispositions and fragile memories.The Illusionist Brain draws on the latest findings in neuroscience to explain how magic deceives us, surprises us, and amazes us, and demonstrates how illusionists skillfully “hack” our brains to alter how we perceive things and influence what we imagine.

Optical illusions. --- Magic tricks. --- Neurosciences. --- Algeria. --- Analysis. --- Behavior. --- Cerebral cortex. --- Cognition. --- Cognitive dissonance. --- Cognitive neuroscience. --- Cryptography. --- Decision-making. --- Everyday life. --- Explanation. --- Fred Kaps. --- French Colonial. --- Genre. --- Grammar. --- Handkerchief. --- Human brain. --- Hypothesis. --- Inference. --- Instance (computer science). --- Learning. --- Long-term memory. --- Magic (illusion). --- Mathematics. --- Metabolism. --- Methods of divination. --- Napoleon III. --- Naturalness (physics). --- Neuron. --- Neuroscience. --- Neuroscientist. --- Opportunism. --- Perception. --- Persi Diaconis. --- Phenomenon. --- Planning. --- Practical reason. --- Problem solving. --- Processing (Chinese materia medica). --- Processing (programming language). --- Psychic. --- Quantity. --- Reason. --- Result. --- Retina. --- Scientist. --- Sense. --- Short-term memory. --- Statistic. --- Theoretician (Marxism). --- Theory. --- Trial and error. --- Visual perception. --- Visual system. --- Western culture. --- Neural sciences --- Neurological sciences --- Neuroscience --- Medical sciences --- Nervous system --- Conjuring --- Legerdemain --- Parlor magic --- Prestidigitation --- Sleight of hand --- Tricks --- Illusions, Optical --- Hallucinations and illusions --- Physiological optics --- Visual perception --- SCIENCE / Life Sciences / Neuroscience --- PSYCHOLOGY / Cognitive Neuroscience & Cognitive Neuropsychology

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The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.

Research & information: general --- Mathematics & science --- large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- n/a

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Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.

depthwise separable convolution (DSC) --- all convolutional network (ACN) --- batch normalization (BN) --- ensemble convolutional neural network (ECNN) --- electrocardiogram (ECG) --- MIT-BIH database --- cephalometric landmark --- X-ray --- deep learning --- ResNet --- registration --- electronic human-machine interface --- blindness --- gesture recognition --- inertial sensors --- IMU --- dynamic contrast-enhanced MRI --- kidney perfusion --- glomerular filtration rate --- pharmacokinetic modeling --- multi-layer perceptron --- parameter estimation --- instance segmentation --- computer vision --- retinal blood vessel image --- computer-aided diagnosis --- U-shaped neural network --- residual learning --- semantic gap --- intracranial hemorrhage --- computed tomography --- random forest --- sleep disorder --- obstructive sleep disorder --- overnight polysomnogram --- EEG --- EMG --- ECG --- HRV signals --- Electronic Medical Record (EMR) --- disease prediction --- Amyotrophic Lateral Sclerosis (ALS) --- weighted Jaccard index (WJI) --- lung cancer --- CT images --- CNN --- pulmonary fibrosis --- radiotherapy --- n/a

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The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications.

large margin nearest neighbor regression --- distance metrics --- prototypes --- evolutionary algorithm --- approximate differential optimization --- multiple point hill climbing --- adaptive sampling --- free radical polymerization --- autonomous driving --- object tracking --- trajectory prediction --- deep neural networks --- stochastic methods --- applied machine learning --- classification and regression --- data mining --- ensemble model --- engineering informatics --- gender-based violence in Mexico --- twitter messages --- class imbalance --- k-nearest neighbor --- instance-based learning --- graph neural network --- deep learning --- hyperparameters --- machine learning --- optimization --- inference --- metaheuristics --- animal-inspired --- exploration --- exploitation --- hot rolled strip steel --- surface defects --- defect classification --- knockout tournament --- dynamic programming algorithm --- computational complexity --- combinatorics --- intelligent transport systems --- traffic control --- spatial-temporal variable speed limit --- multi-agent systems --- reinforcement learning --- distributed W-learning --- urban motorways --- multi-agent framework --- .NET framework --- simulations --- agent-based systems --- agent algorithms --- software design --- multisensory fingerprint --- interoperability --- DeepFKTNet --- classification --- generative adversarial networks --- image classification --- transfer learning --- plastic bottle --- n/a