This book presents a collection of high-quality research papers, presented at the Second International Symposium on Bioinformatics and Biomedicine (BioInfoMed'2022). It offers a comprehensive look into some of the fastest growing fields of science, such as biomedicine, bioinformatics, artificial intelligence, and mathematical modeling. The different chapters of the work include both practical solutions and strictly scientific considerations expanding knowledge about the future bioinformatics and biomedical engineering challenges. We believe that the presented works will have a great impact not only on the development and the application of new methods for modeling, decision making and data mining in healthcare and biomedicine, but also it will provide a source of inspiration for researchers who can implement the proposed methods into their practice and scientific studies.

Presents recent research in Bioinformatics and Biomedical Sciences and Engineering Covers selected and peer-reviewed papers from the Second International Symposium on Bioinformatics and Biomedicine Written by experts in the field

Inhalt
Rhythm Analysis during Cardio-pulmonary Resuscitation with Convolutional and Recurrent Neural Networks Using ECG and Optional Impedance Input.- Parallel Technique on Bidirectional Associative Memory Cohen-Grossberg Neural Network.- Prediction of the Granulometric Composition of the Silt Loading on Transport Arteries in the City of Burgas Based on Artificial Neural Networks.- Emotion Recognition Using Convolutional Neural Network.- An Intuitionistic Fuzzy Estimation Approach to Magnetic Resonance Imaging.- Bioinformatics and Biostatistical Models for Analysis and Prognosis of Antimicrobial Resistance.- Lipid Order of Membranes Isolated from Erythrocytes of Patients with Coronary Artery Disease: Correlation with Biochemical Parameters.- Stress Response of Gram-positive and Gram-negative Bacteria Induced by Metal and Non-Metal Nanoparticles. In Search of Smart Antimicrobial Agents.- Generalized Net Model of Rehabilitation Algorithm for Patients with Proximal Humeral Fracture after Surgical Treatment.- A Generalized Net Model of Time-Delay Recurrent Neural Networks with the Stochastic Gradient Descent and Dropout Algorithm.