596 related articles for article (PubMed ID: 35178119)
1. Investigating the Role of Image Fusion in Brain Tumor Classification Models Based on Machine Learning Algorithm for Personalized Medicine.
Nanmaran R; Srimathi S; Yamuna G; Thanigaivel S; Vickram AS; Priya AK; Karthick A; Karpagam J; Mohanavel V; Muhibbullah M
Comput Math Methods Med; 2022; 2022():7137524. PubMed ID: 35178119
[TBL] [Abstract][Full Text] [Related]
2. An Improved Brain MRI Classification Methodology Based on Statistical Features and Machine Learning Algorithms.
Fayaz M; Qureshi MS; Kussainova K; Burkanova B; Aljarbouh A; Qureshi MB
Comput Math Methods Med; 2021; 2021():8608305. PubMed ID: 34917168
[TBL] [Abstract][Full Text] [Related]
3. An Efficient Cancer Classification Model for CT/MRI/PET Fused Images.
Srimathi S; Yamuna G; Nanmaran R
Curr Med Imaging; 2021; 17(3):319-330. PubMed ID: 32598263
[TBL] [Abstract][Full Text] [Related]
4. An Intelligent Diagnosis Method of Brain MRI Tumor Segmentation Using Deep Convolutional Neural Network and SVM Algorithm.
Wu W; Li D; Du J; Gao X; Gu W; Zhao F; Feng X; Yan H
Comput Math Methods Med; 2020; 2020():6789306. PubMed ID: 32733596
[TBL] [Abstract][Full Text] [Related]
5. Self-attention-based generative adversarial network optimized with color harmony algorithm for brain tumor classification.
S SP; A S; T K; S D
Electromagn Biol Med; 2024 Apr; 43(1-2):31-45. PubMed ID: 38369844
[TBL] [Abstract][Full Text] [Related]
6. A novel extended Kalman filter with support vector machine based method for the automatic diagnosis and segmentation of brain tumors.
Chen B; Zhang L; Chen H; Liang K; Chen X
Comput Methods Programs Biomed; 2021 Mar; 200():105797. PubMed ID: 33317871
[TBL] [Abstract][Full Text] [Related]
7. Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques.
Thirunavukkarasu U; Umapathy S; Ravi V; Alahmadi TJ
Sci Rep; 2024 Jun; 14(1):14571. PubMed ID: 38914599
[TBL] [Abstract][Full Text] [Related]
8. Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review.
Buchlak QD; Esmaili N; Leveque JC; Bennett C; Farrokhi F; Piccardi M
J Clin Neurosci; 2021 Jul; 89():177-198. PubMed ID: 34119265
[TBL] [Abstract][Full Text] [Related]
9. Application of machine learning classifiers to X-ray diffraction imaging with medically relevant phantoms.
Stryker S; Kapadia AJ; Greenberg JA
Med Phys; 2022 Jan; 49(1):532-546. PubMed ID: 34799852
[TBL] [Abstract][Full Text] [Related]
10. Improving the Accuracy of Ensemble Machine Learning Classification Models Using a Novel Bit-Fusion Algorithm for Healthcare AI Systems.
Mishra S; Shaw K; Mishra D; Patil S; Kotecha K; Kumar S; Bajaj S
Front Public Health; 2022; 10():858282. PubMed ID: 35602150
[TBL] [Abstract][Full Text] [Related]
11. Developing a Recognition System for Diagnosing Melanoma Skin Lesions Using Artificial Intelligence Algorithms.
Alsaade FW; Aldhyani THH; Al-Adhaileh MH
Comput Math Methods Med; 2021; 2021():9998379. PubMed ID: 34055044
[TBL] [Abstract][Full Text] [Related]
12. Classification of Benign and Malignant Breast Masses on Mammograms for Large Datasets using Core Vector Machines.
Jebamony J; Jacob D
Curr Med Imaging; 2020; 16(6):703-710. PubMed ID: 32723242
[TBL] [Abstract][Full Text] [Related]
13. Efficient Prediction of Missed Clinical Appointment Using Machine Learning.
Qureshi Z; Maqbool A; Mirza A; Iqbal MZ; Afzal F; Kanubala DD; Rana T; Umair MY; Wakeel A; Shah SK
Comput Math Methods Med; 2021; 2021():2376391. PubMed ID: 34721656
[TBL] [Abstract][Full Text] [Related]
14. Machine learning study of several classifiers trained with texture analysis features to differentiate benign from malignant soft-tissue tumors in T1-MRI images.
Juntu J; Sijbers J; De Backer S; Rajan J; Van Dyck D
J Magn Reson Imaging; 2010 Mar; 31(3):680-9. PubMed ID: 20187212
[TBL] [Abstract][Full Text] [Related]
15. Score and Correlation Coefficient-Based Feature Selection for Predicting Heart Failure Diagnosis by Using Machine Learning Algorithms.
Senan EM; Abunadi I; Jadhav ME; Fati SM
Comput Math Methods Med; 2021; 2021():8500314. PubMed ID: 34966445
[TBL] [Abstract][Full Text] [Related]
16. Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images.
Ferjaoui R; Cherni MA; Boujnah S; Kraiem NEH; Kraiem T
Comput Methods Programs Biomed; 2021 Sep; 209():106320. PubMed ID: 34390938
[TBL] [Abstract][Full Text] [Related]
17. Research of Multimodal Medical Image Fusion Based on Parameter-Adaptive Pulse-Coupled Neural Network and Convolutional Sparse Representation.
Xia J; Lu Y; Tan L
Comput Math Methods Med; 2020; 2020():3290136. PubMed ID: 32411280
[TBL] [Abstract][Full Text] [Related]
18. Machine Learning and Image Processing Enabled Evolutionary Framework for Brain MRI Analysis for Alzheimer's Disease Detection.
Kamal M; Pratap AR; Naved M; Zamani AS; Nancy P; Ritonga M; Shukla SK; Sammy F
Comput Intell Neurosci; 2022; 2022():5261942. PubMed ID: 35419043
[TBL] [Abstract][Full Text] [Related]
19. MRI Brain Tumour Segmentation Using Hybrid Clustering and Classification by Back Propagation Algorithm.
M M; P S
Asian Pac J Cancer Prev; 2018 Nov; 19(11):3257-3263. PubMed ID: 30486629
[TBL] [Abstract][Full Text] [Related]
20. Automated Brain Tumour Detection and Classification using Deep Features and Bayesian Optimised Classifiers.
Kumar SA; Sasikala S
Curr Med Imaging; 2023 Mar; ():. PubMed ID: 37018527
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
