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    The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

    Published 2025-03-01
    “…Moreover, challenges such as algorithmic bias, generalizability across diverse populations, and the necessity for clinician training must be carefully considered. …”
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    A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning by Mostafa Zakeri, Amirhossein Atef, Mohammad Aziznia, Azadeh Jafari

    Published 2024-07-01
    “…To achieve this, we leverage a comprehensive dataset that incorporates clinical and morphological data extracted from 3D real geometries of previous patients. The aim of this research is to provide valuable insights that can help make informed decisions during the treatment process and potentially save the lives of future patients. …”
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    Ambulatory electrocardiographic monitoring in patients with Fabry disease: study design and cohort characterization by E. V. Kotelnikova, V. N. Senchikhin, T. P. Lipchanskaya

    Published 2023-01-01
    “…For effective management of FD, additional multicenter studies are required to develop algorithms for making tactical decisions in the process of cardiac monitoring, taking into account the characteristics of the cardiovascular manifestations of this disease. …”
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    Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur, Gurjit S. Randhawa, Farhat Abbas, Mumtaz Ali, Travis J. Esau, Aitazaz A. Farooque, Rajandeep Singh

    Published 2024-01-01
    “…The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. …”
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    Transferring Learned ECG Representations for Deep Neural Network Classification of Atrial Fibrillation with Photoplethysmography by Jayroop Ramesh, Zahra Solatidehkordi, Raafat Aburukba, Assim Sagahyroon, Fadi Aloul

    Published 2025-04-01
    “…However, the scarcity of large-scale public PPG datasets acquired from wearable devices hinders the development of intelligent automatic AF detection algorithms unaffected by motion artifacts, saturated ambient noise, inter- and intra-subject differences, or limited training data. …”
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