253 related articles for article (PubMed ID: 33828178)
1. Development of machine learning model for diagnostic disease prediction based on laboratory tests.
Park DJ; Park MW; Lee H; Kim YJ; Kim Y; Park YH
Sci Rep; 2021 Apr; 11(1):7567. PubMed ID: 33828178
[TBL] [Abstract][Full Text] [Related]
2. Deep learning assisted detection of glaucomatous optic neuropathy and potential designs for a generalizable model.
Ko YC; Wey SY; Chen WT; Chang YF; Chen MJ; Chiou SH; Liu CJ; Lee CY
PLoS One; 2020; 15(5):e0233079. PubMed ID: 32407355
[TBL] [Abstract][Full Text] [Related]
3. Use of extreme gradient boosting, light gradient boosting machine, and deep neural networks to evaluate the activity stage of extraocular muscles in thyroid-associated ophthalmopathy.
Li Y; Ma J; Xiao J; Wang Y; He W
Graefes Arch Clin Exp Ophthalmol; 2024 Jan; 262(1):203-210. PubMed ID: 37773288
[TBL] [Abstract][Full Text] [Related]
4. A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.
Dinh A; Miertschin S; Young A; Mohanty SD
BMC Med Inform Decis Mak; 2019 Nov; 19(1):211. PubMed ID: 31694707
[TBL] [Abstract][Full Text] [Related]
5. Who's your data? Primary immune deficiency differential diagnosis prediction via machine learning and data mining of the USIDNET registry.
Méndez Barrera JA; Rocha Guzmán S; Hierro Cascajares E; Garabedian EK; Fuleihan RL; Sullivan KE; Lugo Reyes SO
Clin Immunol; 2023 Oct; 255():109759. PubMed ID: 37678719
[TBL] [Abstract][Full Text] [Related]
6. Machine learning approaches to predict peak demand days of cardiovascular admissions considering environmental exposure.
Qiu H; Luo L; Su Z; Zhou L; Wang L; Chen Y
BMC Med Inform Decis Mak; 2020 May; 20(1):83. PubMed ID: 32357880
[TBL] [Abstract][Full Text] [Related]
7. DeepStack-DTIs: Predicting Drug-Target Interactions Using LightGBM Feature Selection and Deep-Stacked Ensemble Classifier.
Zhang Y; Jiang Z; Chen C; Wei Q; Gu H; Yu B
Interdiscip Sci; 2022 Jun; 14(2):311-330. PubMed ID: 34731411
[TBL] [Abstract][Full Text] [Related]
8. Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features.
Hu X; Gong J; Zhou W; Li H; Wang S; Wei M; Peng W; Gu Y
Phys Med Biol; 2021 Mar; 66(6):065015. PubMed ID: 33596552
[TBL] [Abstract][Full Text] [Related]
9. Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.
Lin C; Hsu CJ; Lou YS; Yeh SJ; Lee CC; Su SL; Chen HC
J Med Internet Res; 2017 Nov; 19(11):e380. PubMed ID: 29109070
[TBL] [Abstract][Full Text] [Related]
10. Comparison of machine and deep learning for the classification of cervical cancer based on cervicography images.
Park YR; Kim YJ; Ju W; Nam K; Kim S; Kim KG
Sci Rep; 2021 Aug; 11(1):16143. PubMed ID: 34373589
[TBL] [Abstract][Full Text] [Related]
11. Machine learning models in breast cancer survival prediction.
Montazeri M; Montazeri M; Montazeri M; Beigzadeh A
Technol Health Care; 2016; 24(1):31-42. PubMed ID: 26409558
[TBL] [Abstract][Full Text] [Related]
12. Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.
Song Y; Zhang YD; Yan X; Liu H; Zhou M; Hu B; Yang G
J Magn Reson Imaging; 2018 Dec; 48(6):1570-1577. PubMed ID: 29659067
[TBL] [Abstract][Full Text] [Related]
13. Automated ICD coding for primary diagnosis via clinically interpretable machine learning.
Diao X; Huo Y; Zhao S; Yuan J; Cui M; Wang Y; Lian X; Zhao W
Int J Med Inform; 2021 Sep; 153():104543. PubMed ID: 34391016
[TBL] [Abstract][Full Text] [Related]
14. Development of machine learning models for diagnosis of glaucoma.
Kim SJ; Cho KJ; Oh S
PLoS One; 2017; 12(5):e0177726. PubMed ID: 28542342
[TBL] [Abstract][Full Text] [Related]
15. Comparing deep neural network and other machine learning algorithms for stroke prediction in a large-scale population-based electronic medical claims database.
Chen-Ying Hung ; Wei-Chen Chen ; Po-Tsun Lai ; Ching-Heng Lin ; Chi-Chun Lee
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():3110-3113. PubMed ID: 29060556
[TBL] [Abstract][Full Text] [Related]
16. A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA.
Zheng HL; An SY; Qiao BJ; Guan P; Huang DS; Wu W
Environ Sci Pollut Res Int; 2023 Jan; 30(5):13648-13659. PubMed ID: 36131178
[TBL] [Abstract][Full Text] [Related]
17. Predicting post-stroke pneumonia using deep neural network approaches.
Ge Y; Wang Q; Wang L; Wu H; Peng C; Wang J; Xu Y; Xiong G; Zhang Y; Yi Y
Int J Med Inform; 2019 Dec; 132():103986. PubMed ID: 31629312
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Prediction of admission in pediatric emergency department with deep neural networks and triage textual data.
Roquette BP; Nagano H; Marujo EC; Maiorano AC
Neural Netw; 2020 Jun; 126():170-177. PubMed ID: 32240912
[TBL] [Abstract][Full Text] [Related]
20. Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning-based radiomics.
Mao B; Zhang L; Ning P; Ding F; Wu F; Lu G; Geng Y; Ma J
Eur Radiol; 2020 Dec; 30(12):6924-6932. PubMed ID: 32696256
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]