Sökning: "Atrial Fibrillation detection"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden Atrial Fibrillation detection.

  1. 1. Predicting and classifying atrial fibrillation from ECG recordings using machine learning

    Master-uppsats, Uppsala universitet/Institutionen för biologisk grundutbildning

    Författare :Carl Bogstedt; [2023]
    Nyckelord :Bioinformatics; Machine Learning; Electrocardiogram; Classification; Rough Sets; XGBoost; Atrial Fibrillation;

    Sammanfattning : Atrial fibrillation is one of the most common types of heart arrhythmias, which can cause irregular, weak and fast atrial contractions up to 600 beats per minute. Atrial fibrillation has increased prevalence with age and is associated with increased risks of ischemia, as blood clots can form due to the weak contractions. LÄS MER

  3. 2. MODELING AND EVALUATING AN INTELLIGENT HEALTH MONITORING SYSTEM FOR ATRIAL FIBRILLATION DETECTION

    Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Petter Nordin; [2022]
    Nyckelord :;

    Sammanfattning : The heart disease Atrial Fibrillation (AFib) has increased worldwide in recent years. Untreated AFib can lead to cardiovascular complications such as stroke and heart failure. AFib is detected by physicians using Electrocardiogram (ECG). Since this disease can occur without symptoms for some patients, it can lead to late detection. LÄS MER

  4. 3. Energy-Efficient Detection of Atrial Fibrillation in the Context of Resource-Restrained Devices

    Master-uppsats, Luleå tekniska universitet/Datavetenskap

    Författare :Mansour Kheffache; [2019]
    Nyckelord :IoT; machine learning; atrial fibrillation; ECG; energy-efficiency; hyperdimensional computing; stochastic computing; RVFL; edge computing;

    Sammanfattning : eHealth is a recently emerging practice at the intersection between the ICT and healthcare fields where computing and communication technology is used to improve the traditional healthcare processes or create new opportunities to provide better health services, and eHealth can be considered under the umbrella of the Internet of Things. A common practice in eHealth is the use of machine learning for a computer-aided diagnosis, where an algorithm would be fed some biomedical signal to provide a diagnosis, in the same way a trained radiologist would do. LÄS MER

  5. 4. Non-vitamin K dependent oral anticoagulants (NOACs) controls

    Master-uppsats, Linköpings universitet/Institutionen för fysik, kemi och biologi

    Författare :Anna Persson; [2018]
    Nyckelord :Product development; assay controls;

    Sammanfattning : In recent years non-vitamin K dependent oral anticoagulants (NOACs) have started to replace warfarin for treatment and prevention of deep venous thrombosis (DVT), pulmonary embolism (PE) and stroke in patients with and without atrial fibrillation. There is a need for a simple and rapid method to detect the presence of these drugs in patient plasma. LÄS MER

  7. 5. Machine Learning assisted system for the resource-constrained atrial fibrillation detection from short single-lead ECG signals

    Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Anara Abdukalikova; [2018]
    Nyckelord :E-Health; Atrial Fibrillation detection; ECG; Machine Learning; Recursive Feature Elimination; Sustainability;

    Sammanfattning : An integration of ICT advances into a conventional healthcare system is spreading extensively nowadays. This trend is known as Electronic health or E-Health. E-Health solutions help to achieve the sustainability goal of increasing the expected lifetime while improving the quality of life by providing a constant healthcare monitoring. LÄS MER