201 related articles for article (PubMed ID: 32445550)
21. Prediction of coronary thin-cap fibroatheroma by intravascular ultrasound-based machine learning.
Bae Y; Kang SJ; Kim G; Lee JG; Min HS; Cho H; Kang DY; Lee PH; Ahn JM; Park DW; Lee SW; Kim YH; Lee CW; Park SW; Park SJ
Atherosclerosis; 2019 Sep; 288():168-174. PubMed ID: 31130215
[TBL] [Abstract][Full Text] [Related]
22. Osteoporosis risk prediction using machine learning and conventional methods.
Kim SK; Yoo TK; Oh E; Kim DW
Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():188-91. PubMed ID: 24109656
[TBL] [Abstract][Full Text] [Related]
23. Computer-Aided Diagnosis of Multiple Sclerosis Using a Support Vector Machine and Optical Coherence Tomography Features.
Cavaliere C; Vilades E; Alonso-Rodríguez MC; Rodrigo MJ; Pablo LE; Miguel JM; López-Guillén E; Morla EMS; Boquete L; Garcia-Martin E
Sensors (Basel); 2019 Dec; 19(23):. PubMed ID: 31816925
[TBL] [Abstract][Full Text] [Related]
24. An Assisted Diagnosis System for Detection of Early Pulmonary Nodule in Computed Tomography Images.
Liu JK; Jiang HY; Gao MD; He CG; Wang Y; Wang P; Ma H; Li Y
J Med Syst; 2017 Feb; 41(2):30. PubMed ID: 28032305
[TBL] [Abstract][Full Text] [Related]
25. Mortality prediction in patients with isolated moderate and severe traumatic brain injury using machine learning models.
Rau CS; Kuo PJ; Chien PC; Huang CY; Hsieh HY; Hsieh CH
PLoS One; 2018; 13(11):e0207192. PubMed ID: 30412613
[TBL] [Abstract][Full Text] [Related]
26. Textural differences between renal cell carcinoma subtypes: Machine learning-based quantitative computed tomography texture analysis with independent external validation.
Kocak B; Yardimci AH; Bektas CT; Turkcanoglu MH; Erdim C; Yucetas U; Koca SB; Kilickesmez O
Eur J Radiol; 2018 Oct; 107():149-157. PubMed ID: 30292260
[TBL] [Abstract][Full Text] [Related]
27. Improving breast cancer risk stratification using resonance-frequency electrical impedance spectroscopy through fusion of multiple classifiers.
Lederman D; Zheng B; Wang X; Wang XH; Gur D
Ann Biomed Eng; 2011 Mar; 39(3):931-45. PubMed ID: 21116847
[TBL] [Abstract][Full Text] [Related]
28. Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms.
Maniruzzaman M; Jahanur Rahman M; Ahammed B; Abedin MM; Suri HS; Biswas M; El-Baz A; Bangeas P; Tsoulfas G; Suri JS
Comput Methods Programs Biomed; 2019 Jul; 176():173-193. PubMed ID: 31200905
[TBL] [Abstract][Full Text] [Related]
29. Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis.
Li W; Huang Y; Zhuang BW; Liu GJ; Hu HT; Li X; Liang JY; Wang Z; Huang XW; Zhang CQ; Ruan SM; Xie XY; Kuang M; Lu MD; Chen LD; Wang W
Eur Radiol; 2019 Mar; 29(3):1496-1506. PubMed ID: 30178143
[TBL] [Abstract][Full Text] [Related]
30. Fusion of quantitative imaging features and serum biomarkers to improve performance of computer-aided diagnosis scheme for lung cancer: A preliminary study.
Gong J; Liu JY; Jiang YJ; Sun XW; Zheng B; Nie SD
Med Phys; 2018 Dec; 45(12):5472-5481. PubMed ID: 30317652
[TBL] [Abstract][Full Text] [Related]
31. Comparison of machine learning methods for the detection of focal cortical dysplasia lesions: decision tree, support vector machine and artificial neural network.
Ganji Z; Aghaee Hakak M; Zare H
Neurol Res; 2022 Dec; 44(12):1142-1149. PubMed ID: 35981138
[TBL] [Abstract][Full Text] [Related]
32. A comparative study of machine learning classifiers for risk prediction of asthma disease.
Ullah R; Khan S; Ali H; Chaudhary II; Bilal M; Ahmad I
Photodiagnosis Photodyn Ther; 2019 Dec; 28():292-296. PubMed ID: 31614223
[TBL] [Abstract][Full Text] [Related]
33. Impact of pixel-based machine-learning techniques on automated frameworks for delineation of gross tumor volume regions for stereotactic body radiation therapy.
Kawata Y; Arimura H; Ikushima K; Jin Z; Morita K; Tokunaga C; Yabu-Uchi H; Shioyama Y; Sasaki T; Honda H; Sasaki M
Phys Med; 2017 Oct; 42():141-149. PubMed ID: 29173908
[TBL] [Abstract][Full Text] [Related]
34. 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]
35. Computational Discrimination of Breast Cancer for Korean Women Based on Epidemiologic Data Only.
Lee C; Lee JC; Park B; Bae J; Lim MH; Kang D; Yoo KY; Park SK; Kim Y; Kim S
J Korean Med Sci; 2015 Aug; 30(8):1025-34. PubMed ID: 26240478
[TBL] [Abstract][Full Text] [Related]
36. Fetal health status prediction based on maternal clinical history using machine learning techniques.
Akbulut A; Ertugrul E; Topcu V
Comput Methods Programs Biomed; 2018 Sep; 163():87-100. PubMed ID: 30119860
[TBL] [Abstract][Full Text] [Related]
37. Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening.
Tu SJ; Wang CW; Pan KT; Wu YC; Wu CT
Phys Med Biol; 2018 Mar; 63(6):065005. PubMed ID: 29446758
[TBL] [Abstract][Full Text] [Related]
38. Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours.
Hu J; Zhao Y; Li M; Liu Y; Wang F; Weng Q; You R; Cao D
Eur J Radiol; 2020 May; 126():108929. PubMed ID: 32169748
[TBL] [Abstract][Full Text] [Related]
39. Assessing Breast Cancer Risk with an Artificial Neural Network.
Sepandi M; Taghdir M; Rezaianzadeh A; Rahimikazerooni S
Asian Pac J Cancer Prev; 2018 Apr; 19(4):1017-1019. PubMed ID: 29693975
[TBL] [Abstract][Full Text] [Related]
40. Enhancing the security of patients' portals and websites by detecting malicious web crawlers using machine learning techniques.
Hosseini N; Fakhar F; Kiani B; Eslami S
Int J Med Inform; 2019 Dec; 132():103976. PubMed ID: 31606554
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
