132 related articles for article (PubMed ID: 37685321)
1. Hybrid Methods for Fundus Image Analysis for Diagnosis of Diabetic Retinopathy Development Stages Based on Fusion Features.
Alshahrani M; Al-Jabbar M; Senan EM; Ahmed IA; Saif JAM
Diagnostics (Basel); 2023 Aug; 13(17):. PubMed ID: 37685321
[TBL] [Abstract][Full Text] [Related]
2. Hybrid and Deep Learning Approach for Early Diagnosis of Lower Gastrointestinal Diseases.
Fati SM; Senan EM; Azar AT
Sensors (Basel); 2022 May; 22(11):. PubMed ID: 35684696
[TBL] [Abstract][Full Text] [Related]
3. Multi-Method Diagnosis of Blood Microscopic Sample for Early Detection of Acute Lymphoblastic Leukemia Based on Deep Learning and Hybrid Techniques.
Abunadi I; Senan EM
Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214531
[TBL] [Abstract][Full Text] [Related]
4. Automatic Analysis of MRI Images for Early Prediction of Alzheimer's Disease Stages Based on Hybrid Features of CNN and Handcrafted Features.
Khalid A; Senan EM; Al-Wagih K; Al-Azzam MMA; Alkhraisha ZM
Diagnostics (Basel); 2023 May; 13(9):. PubMed ID: 37175045
[TBL] [Abstract][Full Text] [Related]
5. Predicting of diabetic retinopathy development stages of fundus images using deep learning based on combined features.
Shamsan A; Senan EM; Ahmad Shatnawi HS
PLoS One; 2023; 18(10):e0289555. PubMed ID: 37862328
[TBL] [Abstract][Full Text] [Related]
6. Early Diagnosis of Oral Squamous Cell Carcinoma Based on Histopathological Images Using Deep and Hybrid Learning Approaches.
Fati SM; Senan EM; Javed Y
Diagnostics (Basel); 2022 Aug; 12(8):. PubMed ID: 36010249
[TBL] [Abstract][Full Text] [Related]
7. Analyzing Histological Images Using Hybrid Techniques for Early Detection of Multi-Class Breast Cancer Based on Fusion Features of CNN and Handcrafted.
Al-Jabbar M; Alshahrani M; Senan EM; Ahmed IA
Diagnostics (Basel); 2023 May; 13(10):. PubMed ID: 37238243
[TBL] [Abstract][Full Text] [Related]
8. Hybrid Techniques of X-ray Analysis to Predict Knee Osteoarthritis Grades Based on Fusion Features of CNN and Handcrafted.
Khalid A; Senan EM; Al-Wagih K; Ali Al-Azzam MM; Alkhraisha ZM
Diagnostics (Basel); 2023 May; 13(9):. PubMed ID: 37175000
[TBL] [Abstract][Full Text] [Related]
9. Diabetic Retinopathy Detection from Fundus Images of the Eye Using Hybrid Deep Learning Features.
Butt MM; Iskandar DNFA; Abdelhamid SE; Latif G; Alghazo R
Diagnostics (Basel); 2022 Jul; 12(7):. PubMed ID: 35885512
[TBL] [Abstract][Full Text] [Related]
10. Multi-Method Analysis of Histopathological Image for Early Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning and Hybrid Techniques.
Ahmad M; Irfan MA; Sadique U; Haq IU; Jan A; Khattak MI; Ghadi YY; Aljuaid H
Cancers (Basel); 2023 Oct; 15(21):. PubMed ID: 37958422
[TBL] [Abstract][Full Text] [Related]
11. Features extraction using encoded local binary pattern for detection and grading diabetic retinopathy.
Berbar MA
Health Inf Sci Syst; 2022 Dec; 10(1):14. PubMed ID: 35782197
[TBL] [Abstract][Full Text] [Related]
12. Multi-Techniques for Analyzing X-ray Images for Early Detection and Differentiation of Pneumonia and Tuberculosis Based on Hybrid Features.
Ahmed IA; Senan EM; Shatnawi HSA; Alkhraisha ZM; Al-Azzam MMA
Diagnostics (Basel); 2023 Feb; 13(4):. PubMed ID: 36832302
[TBL] [Abstract][Full Text] [Related]
13. Automated identification of diabetic retinopathy stages using digital fundus images.
Nayak J; Bhat PS; Acharya R; Lim CM; Kagathi M
J Med Syst; 2008 Apr; 32(2):107-15. PubMed ID: 18461814
[TBL] [Abstract][Full Text] [Related]
14. A Regression-Based Approach to Diabetic Retinopathy Diagnosis Using Efficientnet.
Vijayan M; S V
Diagnostics (Basel); 2023 Feb; 13(4):. PubMed ID: 36832262
[TBL] [Abstract][Full Text] [Related]
15. Combining transfer learning with retinal lesion features for accurate detection of diabetic retinopathy.
Hassan D; Gill HM; Happe M; Bhatwadekar AD; Hajrasouliha AR; Janga SC
Front Med (Lausanne); 2022; 9():1050436. PubMed ID: 36425113
[TBL] [Abstract][Full Text] [Related]
16. Histopathological Analysis for Detecting Lung and Colon Cancer Malignancies Using Hybrid Systems with Fused Features.
Al-Jabbar M; Alshahrani M; Senan EM; Ahmed IA
Bioengineering (Basel); 2023 Mar; 10(3):. PubMed ID: 36978774
[TBL] [Abstract][Full Text] [Related]
17. Blood Slide Image Analysis to Classify WBC Types for Prediction Haematology Based on a Hybrid Model of CNN and Handcrafted Features.
Olayah F; Senan EM; Ahmed IA; Awaji B
Diagnostics (Basel); 2023 May; 13(11):. PubMed ID: 37296753
[TBL] [Abstract][Full Text] [Related]
18. Segmentation of retinal blood vessels by a novel hybrid technique- Principal Component Analysis (PCA) and Contrast Limited Adaptive Histogram Equalization (CLAHE).
Sidhu RK; Sachdeva J; Katoch D
Microvasc Res; 2023 Jul; 148():104477. PubMed ID: 36746364
[TBL] [Abstract][Full Text] [Related]
19. Detection of diabetic retinopathy using a fusion of textural and ridgelet features of retinal images and sequential minimal optimization classifier.
Ramasamy LK; Padinjappurathu SG; Kadry S; Damaševičius R
PeerJ Comput Sci; 2021; 7():e456. PubMed ID: 34013026
[TBL] [Abstract][Full Text] [Related]
20. Applying supervised contrastive learning for the detection of diabetic retinopathy and its severity levels from fundus images.
Islam MR; Abdulrazak LF; Nahiduzzaman M; Goni MOF; Anower MS; Ahsan M; Haider J; Kowalski M
Comput Biol Med; 2022 Jul; 146():105602. PubMed ID: 35569335
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
