SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

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Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice.

Chagas disease is endemic in Latin America, but the migration of infected individuals makes the condition an increasingly global problem. The authors review the epidemiology, pathogenesis, diagnosis, and treatment of the disease, focusing particularly on the risk stratification and management of patients with Chagas cardiomyopathy. Chagas cardiomyopathy is the most severe and life-threatening manifestation of human Chagas disease—a 'neglected' tropical disease caused by the protozoan parasite Trypanosoma cruzi. The disease is endemic in all continental Latin American countries, but has become a worldwide problem because of migration of infected individuals to developed countries, mainly in Europe and North America. Chagas cardiomyopathy results from the combined effects of persistent parasitism, parasite-driven tissue inflammation, microvascular and neurogenic dysfunction, and autoimmune responses triggered by the infection. Clinical presentation varies widely according to the extent of myocardial damage, and manifests mainly as three basic syndromes that can coexist in an individual patient: heart failure, cardiac arrhythmia, and thromboembolism. NYHA functional class, left ventricular systolic function, and nonsustained ventricular tachycardia are important prognostic markers of the risk of death. Management of Chagas cardiomyopathy focuses on the treatment of the three main syndromes. The use of β-blockers in patients with Chagas disease and heart failure is safe, well tolerated, and should be encouraged. Most specialists and international institutions now recommend specific antitrypanosomal treatment of patients with chronic Chagas disease, even in the absence of evidence obtained from randomized clinical trials. Further research on the management of patients with Chagas cardiomyopathy is necessary.