Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Nawres Khlifa"'
Publikováno v:
IEEE Access, Vol 12, Pp 54382-54396 (2024)
The healthcare fraud detection field is constantly evolving and faces significant challenges, particularly when addressing imbalanced data issues. Previous studies mainly focused on traditional machine learning (ML) techniques, often struggling with
Externí odkaz:
https://doaj.org/article/1fbffb8d46b841b291bd76d99dba9f8b
Publikováno v:
IEEE Access, Vol 12, Pp 40827-40841 (2024)
Arrhythmia detection in electrocardiogram (ECG) signals is a vital aspect of cardiovascular health monitoring. Current automated methods for arrhythmia classification often struggle to attain satisfactory performance in the detection of various heart
Externí odkaz:
https://doaj.org/article/0159319da94b43a9ba5aff142c08bb79
Autor:
Sinda Hosni, Hajer Khachnaoui, Hsouna Mehdi Zgolli, Sonya Mabrouk, Desire Sidibe, Hedi Tabia, Nawres Khlifa
Publikováno v:
IEEE Access, Vol 11, Pp 135435-135448 (2023)
Deep Learning (DL) methods, such as Convolution Neural Networks (CNNs), have shown great potential in diagnosing complex diseases. Among these diseases, Rhegmatogenous Retinal Detachment (RRD) stands out as a critical condition necessitating precise
Externí odkaz:
https://doaj.org/article/5b5afdca8df241d791440aaa5edac2c1
Publikováno v:
IEEE Access, Vol 11, Pp 91157-91172 (2023)
Convolutional Neural Networks (CNNs) are highly regarded in Deep Learning (DL) and have shown promising results in medical image analysis, making them a leading model for Computer-Aided Diagnosis (CAD) systems. Their efficacy extends to the diagnosis
Externí odkaz:
https://doaj.org/article/e1b71cb1b4144a6c8f0df33198960993
Publikováno v:
Scientific African, Vol 20, Iss , Pp e01679- (2023)
Ultrasound has become the main imaging modality for the diagnosis of thyroid nodules. However, opinions issued and decisions taken by doctors are always subjective and depend on the experience of the doctor and his entourage. It is often essential to
Externí odkaz:
https://doaj.org/article/eb0a396ed79a4dad87b4be5740cf7e08
Autor:
Latifa Saidi, Hajer Jomaa, Haddad Zainab, Hsouna Zgolli, Sonia Mabrouk, Désiré Sidibé, Hedi Tabia, Nawres Khlifa
Publikováno v:
International Journal of Biomedical Imaging, Vol 2023 (2023)
Diabetic macular edema (DME) and age-related macular degeneration (AMD) are two common eye diseases. They are often undiagnosed or diagnosed late. This can result in permanent and irreversible vision loss. Therefore, early detection and treatment of
Externí odkaz:
https://doaj.org/article/c6d4e8c9234c4231b3867b7db9c8896b
Publikováno v:
Libyan Journal of Medicine, Vol 17, Iss 1 (2022)
To develop a machine learning (ML) model for the prediction of the idiopathic macular hole (MH) status at 9 months after vitrectomy and inverted flap internal limiting membrane (ILM) peeling surgery. This single center was conducted at Department A,
Externí odkaz:
https://doaj.org/article/d20d85bd8ba64a2d9ae4a9b59f54cbe7
Publikováno v:
Journal of Imaging, Vol 8, Iss 4, p 97 (2022)
Early Parkinson’s Disease (PD) diagnosis is a critical challenge in the treatment process. Meeting this challenge allows appropriate planning for patients. However, Scan Without Evidence of Dopaminergic Deficit (SWEDD) is a heterogeneous group of P
Externí odkaz:
https://doaj.org/article/72a9c14e10794622b82c49f7dce2b8ba
Publikováno v:
Multimedia Tools and Applications. 82:10491-10514
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c709d06a17e5168e4ac0db5ec3a6f7d
https://doi.org/10.1007/s11042-022-13642-0
https://doi.org/10.1007/s11042-022-13642-0
Publikováno v:
WSEAS TRANSACTIONS ON SIGNAL PROCESSING. 18:140-145
Many computer vision applications Computer Aided Diagnosis require an accurate and efficient eye detector. We represent, in this work, an efficient approach for determining the position of the eye in images presenting faces. First, a series of candid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a8744fc42e6e900c138a8b23cebb985
https://doi.org/10.37394/232014.2022.18.20
https://doi.org/10.37394/232014.2022.18.20