Sentiment analysisSentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.
Automatic summarizationAutomatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or relevant information within the original content. Artificial intelligence algorithms are commonly developed and employed to achieve this, specialized for different types of data. Text summarization is usually implemented by natural language processing methods, designed to locate the most informative sentences in a given document.
Text miningText mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al.
Knowledge extractionKnowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, s) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL (data warehouse), the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema.
Supraventricular tachycardiaSupraventricular tachycardia (SVT) is an umbrella term for fast heart rhythms arising from the upper part of the heart. This is in contrast to the other group of fast heart rhythms – ventricular tachycardia, which start within the lower chambers of the heart. There are four main types of SVT: atrial fibrillation, atrial flutter, paroxysmal supraventricular tachycardia (PSVT), and Wolff–Parkinson–White syndrome. The symptoms of SVT include palpitations, feeling of faintness, sweating, shortness of breath, and/or chest pain.
Left bundle branch blockLeft bundle branch block (LBBB) is a conduction abnormality in the heart that can be seen on an electrocardiogram (ECG). In this condition, activation of the left ventricle of the heart is delayed, which causes the left ventricle to contract later than the right ventricle. Among the causes of LBBB are: Aortic stenosis Dilated cardiomyopathy Acute myocardial infarction Extensive coronary artery disease Primary disease of the cardiac electrical conduction system Long standing hypertension leading to aortic root dilatation and subsequent aortic regurgitation Lyme disease Slow or absent conduction through the left bundle branch means that it takes longer than normal for the left ventricle to fully depolarise.
ElectrocardiographyElectrocardiography is the process of producing an electrocardiogram (ECG or EKG ), a recording of the heart's electrical activity through repeated cardiac cycles. It is an electrogram of the heart which is a graph of voltage versus time of the electrical activity of the heart using electrodes placed on the skin. These electrodes detect the small electrical changes that are a consequence of cardiac muscle depolarization followed by repolarization during each cardiac cycle (heartbeat).
Artificial cardiac pacemakerAn artificial cardiac pacemaker (artificial pacemaker, and sometimes just pacemaker, although the term is also used to refer to the body's natural cardiac pacemaker) is a medical device, nowadays always implanted, that generates electrical pulses delivered by electrodes to one or more of the chambers of the heart, the upper atria or lower ventricles. Each pulse causes the targeted chamber(s) to contract and pump blood, thus regulating the function of the electrical conduction system of the heart.
Atrial fibrillationAtrial fibrillation (AF or A-fib) is an abnormal heart rhythm (arrhythmia) characterized by rapid and irregular beating of the atrial chambers of the heart. It often begins as short periods of abnormal beating, which become longer or continuous over time. It may also start as other forms of arrhythmia such as atrial flutter that then transform into AF. Episodes can be asymptomatic. Symptomatic episodes may involve heart palpitations, fainting, lightheadedness, shortness of breath, or chest pain.
Second-degree atrioventricular blockSecond-degree atrioventricular block (AV block) is a disease of the electrical conduction system of the heart. It is a conduction block between the atria and ventricles. The presence of second-degree AV block is diagnosed when one or more (but not all) of the atrial impulses fail to conduct to the ventricles due to impaired conduction. It is classified as a block of the AV node, falling between first-degree (slowed conduction) and third degree blocks (complete block). Most people with Wenckebach (Type I Mobitz) do not show symptoms.
Intraventricular blockAn intraventricular block is a heart conduction disorder — heart block of the ventricles of the heart. An example is a right bundle branch block, right fascicular block, bifascicular block, trifascicular block. Types of intraventricular blocks are Fascicular block Left anterior fascicular block Left posterior fascicular block Trifascicular block Bifascicular block (RBBB with fascicular block) Right bundle branch block (RBBB) Left bundle branch block (LBBB) Intraventricular conduction delays (IVCD) are conduction disorders seen in intraventricular propagation of supraventricular impulses resulting in changes in the QRS complex duration or morphology, or both.
Cardiac arrestCardiac arrest occurs when the heart stops beating. It is defined as cessation of normal circulation of blood due to failure of the heart to pump effectively. It is a medical emergency that, without immediate medical intervention, will result in cardiac death within minutes. When it happens suddenly, it is called sudden cardiac arrest. Cardiopulmonary resuscitation (CPR) and possibly defibrillation are needed until further treatment can be provided. Cardiac arrest results in a rapid loss of consciousness, and breathing may be abnormal or absent.
Variant anginaVariant angina, also known as Prinzmetal angina, vasospastic angina, angina inversa, coronary vessel spasm, or coronary artery vasospasm, is a syndrome typically consisting of angina (cardiac chest pain). Variant angina differs from stable angina in that it commonly occurs in individuals who are at rest or even asleep, whereas stable angina is generally triggered by exertion or intense exercise. Variant angina is caused by vasospasm, a narrowing of the coronary arteries due to contraction of the heart's smooth muscle tissue in the vessel walls.
Signal-averaged electrocardiogramSignal-averaged electrocardiography (SAECG) is a special electrocardiographic technique, in which multiple electric signals from the heart are averaged to remove interference and reveal small variations in the QRS complex, usually the so-called "late potentials". These may represent a predisposition towards potentially dangerous ventricular tachyarrhythmias. A resting electrocardiogram (ECG) is recorded in the supine position using an ECG machine equipped with SAECG software; this can be done by a physician, nurse, or medical technician.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
