**5. Automatic reasoning or machine learning**

Based on contexts of repeating patterns or parameters, it groups and analyzes them and then identifies the behavior or tendency of a certain event or circumstance to suggest different predictions. It is also a specialized tool in extracting stored information to answer questions and draw conclusions to detect patterns, draw conclusions to detect patterns, of certain epidemiological behaviors.

In this area of artificial intelligence, applications were recognized in Education research: digital health: intersections between scientific research and its mediatization. Medical education: opportunities for collaborative work towards artificial intelligence tools in medical education, improvement of pedagogical techniques for learning. Dermatology: diagnosis by dermatoscopy (sonification), laboratory, and prospective observational study. Public health: comparison of the performance of machine learning algorithms in predictive analytics in public health and medicine, predictive and probabilistic models for estimating the risk of health events or diseases. Occupational health: human activity recognitions based on feature selection in the smart home using a backpropagation algorithm. Deep machine learning for workflow recognition during surgery. Occupational medicine: artificial intelligence in occupational medicine. Pneumology: prediction of asthma exacerbations, and chronic disease changes, using algorithms and predictive models of Bayesian classifiers and support vector machines with artificial intelligence Internal medicine: mobile application of intensive insulin therapy based on artificial intelligence techniques. Anesthesiology: artificial intelligence system for endotracheal intubation. Pediatric surgery: preoperative prediction of surgical morbidity in children: comparison of five statistical models, logistic regression models. General surgery: development of an intelligent surgical training system for thoracentesis. Laparoscopic surgery: Analysis and counting of the uses of the multifunctional or modular tool in mixed procedures of cholecystectomies and Nissen judicature to reduce operating room time and decrease patient risk, by means of a video using fuzzy logic techniques, to analyze the types of instruments used, the duration of each use and the function of each instrument. Diagnostics. fuzzy naive Bayesian model for medical diagnostic decision support, medical applications as a

### *Artificial Intelligence Starts the Big Bang of Modern Medicine and Surgery DOI: http://dx.doi.org/10.5772/intechopen.112057*

diagnostic aid in medicine, SOFTEL-MINSAP experience, and segmentation methods based on machine learning algorithms for large-scale magnetic resonance imaging. Technological focus on diagnostic aids for cancerous lesions using learning algorithms. Anatomical diagnosis: stable segmentation based on atlas mapped prior (stamp) machine learning for large-scale multicenter MRI data. Diagnostic Microbiological Metabolic Profiling: predicting colonic polyps with machine learning based on urinary metabolomics. Cardiology: machine learning system to improve heart failure patient care, predicting heart attacks four hours in advance in patients with a history of heart disease with a tendency to myocardial infarction, and improving prediction times for cardiologists. This system was fed with clinical data from each patient, incorporating clinical parameters to make the prediction. Physiotherapy: a computerized behavioral system for home.

physiotherapy exercises using an RGBD camera. Research: artificial intelligence applied to evidence-based surgery. Rheumatology. identifies new pathways associated with demineralization in a viral model of multiple sclerosis, prediction of HIVassociated neurocognitive disorder from three genetic features of the gp 120 glycoprotein envelope, and Molecular biology prediction of interactions between HIV-1 and human proteins by information integration. Genetics prediction of virus mutations by statistical relational learning, Microbiology Genetics virus detection by statistical gene expression analysis, and classification of therapy resistance based on longitudinal biomarker profiles [10–25].
