133 related articles for article (PubMed ID: 38742084)
1. Colon and lung cancer classification from multi-modal images using resilient and efficient neural network architectures.
Uddin AH; Chen YL; Akter MR; Ku CS; Yang J; Por LY
Heliyon; 2024 May; 10(9):e30625. PubMed ID: 38742084
[TBL] [Abstract][Full Text] [Related]
2. A convolution neural network with multi-level convolutional and attention learning for classification of cancer grades and tissue structures in colon histopathological images.
Dabass M; Vashisth S; Vig R
Comput Biol Med; 2022 Aug; 147():105680. PubMed ID: 35671654
[TBL] [Abstract][Full Text] [Related]
3. Deep learning for colon cancer histopathological images analysis.
Ben Hamida A; Devanne M; Weber J; Truntzer C; Derangère V; Ghiringhelli F; Forestier G; Wemmert C
Comput Biol Med; 2021 Sep; 136():104730. PubMed ID: 34375901
[TBL] [Abstract][Full Text] [Related]
4. DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.
Kadirappa R; S D; R P; Ko SB
Microsc Res Tech; 2024 Feb; 87(2):229-256. PubMed ID: 37750465
[TBL] [Abstract][Full Text] [Related]
5. From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histology.
Verma J; Sandhu A; Popli R; Kumar R; Khullar V; Kansal I; Sharma A; Garg K; Kashyap N; Aurangzeb K
Open Life Sci; 2023; 18(1):20220777. PubMed ID: 38152577
[TBL] [Abstract][Full Text] [Related]
6. Color-CADx: a deep learning approach for colorectal cancer classification through triple convolutional neural networks and discrete cosine transform.
Sharkas M; Attallah O
Sci Rep; 2024 Mar; 14(1):6914. PubMed ID: 38519513
[TBL] [Abstract][Full Text] [Related]
7. Histopathology image classification: highlighting the gap between manual analysis and AI automation.
Doğan RS; Yılmaz B
Front Oncol; 2023; 13():1325271. PubMed ID: 38298445
[TBL] [Abstract][Full Text] [Related]
8. Weakly Supervised Learning using Attention gates for colon cancer histopathological image segmentation.
Ben Hamida A; Devanne M; Weber J; Truntzer C; Derangère V; Ghiringhelli F; Forestier G; Wemmert C
Artif Intell Med; 2022 Nov; 133():102407. PubMed ID: 36328667
[TBL] [Abstract][Full Text] [Related]
9. [Methodical approaches to annotation and labeling of histological images in order to automatically detect the layers of the stomach wall and the depth of invasion of gastric cancer].
Mikhailov IA; Khvostikov AV; Krylov AS
Arkh Patol; 2022; 84(6):67-73. PubMed ID: 36469721
[TBL] [Abstract][Full Text] [Related]
10. Enhancing accessibility for improved diagnosis with modified EfficientNetV2-S and cyclic learning rate strategy in women with disabilities and breast cancer.
Al Moteri M; Mahesh TR; Thakur A; Vinoth Kumar V; Khan SB; Alojail M
Front Med (Lausanne); 2024; 11():1373244. PubMed ID: 38515985
[TBL] [Abstract][Full Text] [Related]
11. An Explainable Classification Method Based on Complex Scaling in Histopathology Images for Lung and Colon Cancer.
Tummala S; Kadry S; Nadeem A; Rauf HT; Gul N
Diagnostics (Basel); 2023 Apr; 13(9):. PubMed ID: 37174985
[TBL] [Abstract][Full Text] [Related]
12. Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases.
Ibrahim DM; Elshennawy NM; Sarhan AM
Comput Biol Med; 2021 May; 132():104348. PubMed ID: 33774272
[TBL] [Abstract][Full Text] [Related]
13. Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.
Munuswamy Selvaraj K; Gnanagurusubbiah S; Roby Roy RR; John Peter JH; Balu S
Curr Probl Cancer; 2024 Apr; 49():101077. PubMed ID: 38480028
[TBL] [Abstract][Full Text] [Related]
14. Optimizing double-layered convolutional neural networks for efficient lung cancer classification through hyperparameter optimization and advanced image pre-processing techniques.
Musthafa MM; Manimozhi I; Mahesh TR; Guluwadi S
BMC Med Inform Decis Mak; 2024 May; 24(1):142. PubMed ID: 38802836
[TBL] [Abstract][Full Text] [Related]
15. A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup.
Liu Y; Zhang M; Zhong Z; Zeng X
Med Phys; 2023 Mar; 50(3):1528-1538. PubMed ID: 36057788
[TBL] [Abstract][Full Text] [Related]
16. A feature engineering-based machine learning technique to detect and classify lung and colon cancer from histopathological images.
Chhillar I; Singh A
Med Biol Eng Comput; 2024 Mar; 62(3):913-924. PubMed ID: 38091162
[TBL] [Abstract][Full Text] [Related]
17. IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach.
Chen H; Li C; Li X; Rahaman MM; Hu W; Li Y; Liu W; Sun C; Sun H; Huang X; Grzegorzek M
Comput Biol Med; 2022 Apr; 143():105265. PubMed ID: 35123138
[TBL] [Abstract][Full Text] [Related]
18. Transfer Learning Approach and Nucleus Segmentation with MedCLNet Colon Cancer Database.
Reis HC; Turk V
J Digit Imaging; 2023 Feb; 36(1):306-325. PubMed ID: 36127531
[TBL] [Abstract][Full Text] [Related]
19. MTU: A multi-tasking U-net with hybrid convolutional learning and attention modules for cancer classification and gland Segmentation in Colon Histopathological Images.
Dabass M; Vashisth S; Vig R
Comput Biol Med; 2022 Nov; 150():106095. PubMed ID: 36179516
[TBL] [Abstract][Full Text] [Related]
20. Deep Transfer Learning with Enhanced Feature Fusion for Detection of Abnormalities in X-ray Images.
Alammar Z; Alzubaidi L; Zhang J; Li Y; Lafta W; Gu Y
Cancers (Basel); 2023 Aug; 15(15):. PubMed ID: 37568821
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
