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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.

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 --- n/a