134 related articles for article (PubMed ID: 33846472)
1. Prediction of ambulatory outcome in patients with corona radiata infarction using deep learning.
Kim JK; Choo YJ; Shin H; Choi GS; Chang MC
Sci Rep; 2021 Apr; 11(1):7989. PubMed ID: 33846472
[TBL] [Abstract][Full Text] [Related]
2. Prediction of Stroke Outcome Using Natural Language Processing-Based Machine Learning of Radiology Report of Brain MRI.
Heo TS; Kim YS; Choi JM; Jeong YS; Seo SY; Lee JH; Jeon JP; Kim C
J Pers Med; 2020 Dec; 10(4):. PubMed ID: 33339385
[TBL] [Abstract][Full Text] [Related]
3. Deep Learning Algorithm Trained on Brain Magnetic Resonance Images and Clinical Data to Predict Motor Outcomes of Patients With Corona Radiata Infarct.
Kim JK; Chang MC; Park D
Front Neurosci; 2021; 15():795553. PubMed ID: 35046770
[TBL] [Abstract][Full Text] [Related]
4. Prediction of Motor Outcome of Stroke Patients Using a Deep Learning Algorithm with Brain MRI as Input Data.
Shin H; Kim JK; Choo YJ; Choi GS; Chang MC
Eur Neurol; 2022; 85(6):460-466. PubMed ID: 35738236
[TBL] [Abstract][Full Text] [Related]
5. Predicting motor outcome in preterm infants from very early brain diffusion MRI using a deep learning convolutional neural network (CNN) model.
Saha S; Pagnozzi A; Bourgeat P; George JM; Bradford D; Colditz PB; Boyd RN; Rose SE; Fripp J; Pannek K
Neuroimage; 2020 Jul; 215():116807. PubMed ID: 32278897
[TBL] [Abstract][Full Text] [Related]
6. Prediction of Motor Function in Stroke Patients Using Machine Learning Algorithm: Development of Practical Models.
Kim JK; Choo YJ; Chang MC
J Stroke Cerebrovasc Dis; 2021 Aug; 30(8):105856. PubMed ID: 34022582
[TBL] [Abstract][Full Text] [Related]
7. Deep learning to differentiate parkinsonian disorders separately using single midsagittal MR imaging: a proof of concept study.
Kiryu S; Yasaka K; Akai H; Nakata Y; Sugomori Y; Hara S; Seo M; Abe O; Ohtomo K
Eur Radiol; 2019 Dec; 29(12):6891-6899. PubMed ID: 31264017
[TBL] [Abstract][Full Text] [Related]
8. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm.
Lee JH; Kim DH; Jeong SN; Choi SH
J Dent; 2018 Oct; 77():106-111. PubMed ID: 30056118
[TBL] [Abstract][Full Text] [Related]
9. Multi-input deep learning architecture for predicting breast tumor response to chemotherapy using quantitative MR images.
El Adoui M; Drisis S; Benjelloun M
Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1491-1500. PubMed ID: 32556920
[TBL] [Abstract][Full Text] [Related]
10. Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.
Ha R; Chang P; Mutasa S; Karcich J; Goodman S; Blum E; Kalinsky K; Liu MZ; Jambawalikar S
J Magn Reson Imaging; 2019 Feb; 49(2):518-524. PubMed ID: 30129697
[TBL] [Abstract][Full Text] [Related]
11. A deep learning nomogram kit for predicting metastatic lymph nodes in rectal cancer.
Ding L; Liu G; Zhang X; Liu S; Li S; Zhang Z; Guo Y; Lu Y
Cancer Med; 2020 Dec; 9(23):8809-8820. PubMed ID: 32997900
[TBL] [Abstract][Full Text] [Related]
12. Discriminating pseudoprogression and true progression in diffuse infiltrating glioma using multi-parametric MRI data through deep learning.
Lee J; Wang N; Turk S; Mohammed S; Lobo R; Kim J; Liao E; Camelo-Piragua S; Kim M; Junck L; Bapuraj J; Srinivasan A; Rao A
Sci Rep; 2020 Nov; 10(1):20331. PubMed ID: 33230285
[TBL] [Abstract][Full Text] [Related]
13. Deep-learning approach with convolutional neural network for classification of maximum intensity projections of dynamic contrast-enhanced breast magnetic resonance imaging.
Fujioka T; Yashima Y; Oyama J; Mori M; Kubota K; Katsuta L; Kimura K; Yamaga E; Oda G; Nakagawa T; Kitazume Y; Tateishi U
Magn Reson Imaging; 2021 Jan; 75():1-8. PubMed ID: 33045323
[TBL] [Abstract][Full Text] [Related]
14. A convolutional neural network algorithm for automatic segmentation of head and neck organs at risk using deep lifelong learning.
Chan JW; Kearney V; Haaf S; Wu S; Bogdanov M; Reddick M; Dixit N; Sudhyadhom A; Chen J; Yom SS; Solberg TD
Med Phys; 2019 May; 46(5):2204-2213. PubMed ID: 30887523
[TBL] [Abstract][Full Text] [Related]
15. Combined Transfer Learning and Test-Time Augmentation Improves Convolutional Neural Network-Based Semantic Segmentation of Prostate Cancer from Multi-Parametric MR Images.
Hoar D; Lee PQ; Guida A; Patterson S; Bowen CV; Merrimen J; Wang C; Rendon R; Beyea SD; Clarke SE
Comput Methods Programs Biomed; 2021 Oct; 210():106375. PubMed ID: 34500139
[TBL] [Abstract][Full Text] [Related]
16. Deep learning in rare disease. Detection of tubers in tuberous sclerosis complex.
Sánchez Fernández I; Yang E; Calvachi P; Amengual-Gual M; Wu JY; Krueger D; Northrup H; Bebin ME; Sahin M; Yu KH; Peters JM;
PLoS One; 2020; 15(4):e0232376. PubMed ID: 32348367
[TBL] [Abstract][Full Text] [Related]
17. A deep learning approach for sepsis monitoring via severity score estimation.
Aşuroğlu T; Oğul H
Comput Methods Programs Biomed; 2021 Jan; 198():105816. PubMed ID: 33157471
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning-Derived High-Level Neuroimaging Features Predict Clinical Outcomes for Large Vessel Occlusion.
Nishi H; Oishi N; Ishii A; Ono I; Ogura T; Sunohara T; Chihara H; Fukumitsu R; Okawa M; Yamana N; Imamura H; Sadamasa N; Hatano T; Nakahara I; Sakai N; Miyamoto S
Stroke; 2020 May; 51(5):1484-1492. PubMed ID: 32248769
[TBL] [Abstract][Full Text] [Related]
19. Prediction of Response to Stereotactic Radiosurgery for Brain Metastases Using Convolutional Neural Networks.
Cha YJ; Jang WI; Kim MS; Yoo HJ; Paik EK; Jeong HK; Youn SM
Anticancer Res; 2018 Sep; 38(9):5437-5445. PubMed ID: 30194200
[TBL] [Abstract][Full Text] [Related]
20. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.
Urban G; Tripathi P; Alkayali T; Mittal M; Jalali F; Karnes W; Baldi P
Gastroenterology; 2018 Oct; 155(4):1069-1078.e8. PubMed ID: 29928897
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]