Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Cardiac stress testA cardiac stress test (also referred to as a cardiac diagnostic test, cardiopulmonary exercise test, or abbreviated CPX test) is a cardiological test that measures the heart's ability to respond to external stress in a controlled clinical environment. The stress response is induced by exercise or by intravenous pharmacological stimulation. Cardiac stress tests compare the coronary circulation while the patient is at rest with the same patient's circulation during maximum cardiac exertion, showing any abnormal blood flow to the myocardium (heart muscle tissue).
Brugada syndromeBrugada syndrome (BrS) is a genetic disorder in which the electrical activity of the heart is abnormal due to channelopathy. It increases the risk of abnormal heart rhythms and sudden cardiac death. Those affected may have episodes of syncope. The abnormal heart rhythms seen in those with Brugada syndrome often occur at rest. They may be triggered by a fever. About a quarter of those with Brugada syndrome have a family member who also has the condition. Some cases may be due to a new genetic mutation or certain medications.
Dimensionality reductionDimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally close to its intrinsic dimension. Working in high-dimensional spaces can be undesirable for many reasons; raw data are often sparse as a consequence of the curse of dimensionality, and analyzing the data is usually computationally intractable (hard to control or deal with).
Computational scienceComputational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of science that uses advanced computing capabilities to understand and solve complex physical problems. This includes Algorithms (numerical and non-numerical): mathematical models, computational models, and computer simulations developed to solve sciences (e.
Nonlinear system identificationSystem identification is a method of identifying or measuring the mathematical model of a system from measurements of the system inputs and outputs. The applications of system identification include any system where the inputs and outputs can be measured and include industrial processes, control systems, economic data, biology and the life sciences, medicine, social systems and many more. A nonlinear system is defined as any system that is not linear, that is any system that does not satisfy the superposition principle.
Problem solvingProblem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields. The former is an example of simple problem solving (SPS) addressing one issue, whereas the latter is complex problem solving (CPS) with multiple interrelated obstacles.
ElectrophysiologyElectrophysiology (from Greek ἥλεκτ, ēlektron, "amber" [see the etymology of "electron"]; φύσις, physis, "nature, origin"; and -λογία, -logia) is the branch of physiology that studies the electrical properties of biological cells and tissues. It involves measurements of voltage changes or electric current or manipulations on a wide variety of scales from single ion channel proteins to whole organs like the heart. In neuroscience, it includes measurements of the electrical activity of neurons, and, in particular, action potential activity.
Deep reinforcement learningDeep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to make decisions by trial and error. Deep RL incorporates deep learning into the solution, allowing agents to make decisions from unstructured input data without manual engineering of the state space. Deep RL algorithms are able to take in very large inputs (e.g.
Torsades de pointesTorsades de pointes, torsade de pointes or torsades des pointes (TdP) (tɔːˌsɑːd_də_ˈpwãt, tɔʁsad də pwɛ̃t̪, translated as "twisting of peaks") is a specific type of abnormal heart rhythm that can lead to sudden cardiac death. It is a polymorphic ventricular tachycardia that exhibits distinct characteristics on the electrocardiogram (ECG). It was described by French physician François Dessertenne in 1966. Prolongation of the QT interval can increase a person's risk of developing this abnormal heart rhythm, occurring in between 1% and 10% of patients who receive QT-prolonging antiarrhythmic drugs.
