142 related articles for article (PubMed ID: 30258856)
1. Distinction between phyllodes tumor and fibroadenoma in breast ultrasound using deep learning image analysis.
Stoffel E; Becker AS; Wurnig MC; Marcon M; Ghafoor S; Berger N; Boss A
Eur J Radiol Open; 2018; 5():165-170. PubMed ID: 30258856
[TBL] [Abstract][Full Text] [Related]
2. Differentiation between Phyllodes Tumors and Fibroadenomas through Breast Ultrasound: Deep-Learning Model Outperforms Ultrasound Physicians.
Shi Z; Ma Y; Ma X; Jin A; Zhou J; Li N; Sheng D; Chang C; Chen J; Li J
Sensors (Basel); 2023 May; 23(11):. PubMed ID: 37299826
[TBL] [Abstract][Full Text] [Related]
3. Diagnostic Value of Breast Lesions Between Deep Learning-Based Computer-Aided Diagnosis System and Experienced Radiologists: Comparison the Performance Between Symptomatic and Asymptomatic Patients.
Xiao M; Zhao C; Li J; Zhang J; Liu H; Wang M; Ouyang Y; Zhang Y; Jiang Y; Zhu Q
Front Oncol; 2020; 10():1070. PubMed ID: 32733799
[No Abstract] [Full Text] [Related]
4. Application of deep learning to establish a diagnostic model of breast lesions using two-dimensional grayscale ultrasound imaging.
Zhang N; Li XT; Ma L; Fan ZQ; Sun YS
Clin Imaging; 2021 Nov; 79():56-63. PubMed ID: 33887507
[TBL] [Abstract][Full Text] [Related]
5. Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study.
Becker AS; Mueller M; Stoffel E; Marcon M; Ghafoor S; Boss A
Br J Radiol; 2018 Feb; 91(1083):20170576. PubMed ID: 29215311
[TBL] [Abstract][Full Text] [Related]
6. Differential diagnosis between small breast phyllodes tumors and fibroadenomas using artificial intelligence and ultrasound data.
Niu S; Huang J; Li J; Liu X; Wang D; Wang Y; Shen H; Qi M; Xiao Y; Guan M; Li D; Liu F; Wang X; Xiong Y; Gao S; Wang X; Yu P; Zhu J
Quant Imaging Med Surg; 2021 May; 11(5):2052-2061. PubMed ID: 33936986
[TBL] [Abstract][Full Text] [Related]
7. Artificial Intelligence Algorithm Detecting Lung Infection in Supine Chest Radiographs of Critically Ill Patients With a Diagnostic Accuracy Similar to Board-Certified Radiologists.
Rueckel J; Kunz WG; Hoppe BF; Patzig M; Notohamiprodjo M; Meinel FG; Cyran CC; Ingrisch M; Ricke J; Sabel BO
Crit Care Med; 2020 Jul; 48(7):e574-e583. PubMed ID: 32433121
[TBL] [Abstract][Full Text] [Related]
8. Texture Analysis of Ultrasound Images to Differentiate Simple Fibroadenomas From Complex Fibroadenomas and Benign Phyllodes Tumors.
Basara Akin I; Ozgul H; Simsek K; Altay C; Secil M; Balci P
J Ultrasound Med; 2020 Oct; 39(10):1993-2003. PubMed ID: 32329531
[TBL] [Abstract][Full Text] [Related]
9. Impact of radiomics on the breast ultrasound radiologist's clinical practice: From lumpologist to data wrangler.
Fleury EFC; Marcomini K
Eur J Radiol; 2020 Oct; 131():109197. PubMed ID: 32795725
[TBL] [Abstract][Full Text] [Related]
10. Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network.
Fujioka T; Kubota K; Mori M; Kikuchi Y; Katsuta L; Kasahara M; Oda G; Ishiba T; Nakagawa T; Tateishi U
Jpn J Radiol; 2019 Jun; 37(6):466-472. PubMed ID: 30888570
[TBL] [Abstract][Full Text] [Related]
11. Ultrasonography and core needle biopsy in the differential diagnosis of fibroadenoma and tumor phyllodes.
Bode MK; Rissanen T; Apaja-Sarkkinen M
Acta Radiol; 2007 Sep; 48(7):708-13. PubMed ID: 17728999
[TBL] [Abstract][Full Text] [Related]
12. Differentiation between phyllodes tumor and fibroadenoma using real-time elastography.
Adamietz BR; Kahmann L; Fasching PA; Schulz-Wendtland R; Uder M; Beckmann MW; Meier-Meitinger M
Ultraschall Med; 2011 Dec; 32 Suppl 2():E75-9. PubMed ID: 22194044
[TBL] [Abstract][Full Text] [Related]
13. A five-gene reverse transcription-PCR assay for pre-operative classification of breast fibroepithelial lesions.
Tan WJ; Cima I; Choudhury Y; Wei X; Lim JC; Thike AA; Tan MH; Tan PH
Breast Cancer Res; 2016 Mar; 18(1):31. PubMed ID: 26961242
[TBL] [Abstract][Full Text] [Related]
14. Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.
Liu H; Li L; Wormstone IM; Qiao C; Zhang C; Liu P; Li S; Wang H; Mou D; Pang R; Yang D; Zangwill LM; Moghimi S; Hou H; Bowd C; Jiang L; Chen Y; Hu M; Xu Y; Kang H; Ji X; Chang R; Tham C; Cheung C; Ting DSW; Wong TY; Wang Z; Weinreb RN; Xu M; Wang N
JAMA Ophthalmol; 2019 Dec; 137(12):1353-1360. PubMed ID: 31513266
[TBL] [Abstract][Full Text] [Related]
15. Distinction of phyllodes tumor from fibroadenoma: a reappraisal of an old problem.
Krishnamurthy S; Ashfaq R; Shin HJ; Sneige N
Cancer; 2000 Dec; 90(6):342-9. PubMed ID: 11156517
[TBL] [Abstract][Full Text] [Related]
16. Immunohistochemical study of MIB1 expression in phyllodes tumor and fibroadenoma.
Umekita Y; Yoshida H
Pathol Int; 1999 Sep; 49(9):807-10. PubMed ID: 10504552
[TBL] [Abstract][Full Text] [Related]
17. Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet.
Bien N; Rajpurkar P; Ball RL; Irvin J; Park A; Jones E; Bereket M; Patel BN; Yeom KW; Shpanskaya K; Halabi S; Zucker E; Fanton G; Amanatullah DF; Beaulieu CF; Riley GM; Stewart RJ; Blankenberg FG; Larson DB; Jones RH; Langlotz CP; Ng AY; Lungren MP
PLoS Med; 2018 Nov; 15(11):e1002699. PubMed ID: 30481176
[TBL] [Abstract][Full Text] [Related]
18. Evaluating the Accuracy of Breast Cancer and Molecular Subtype Diagnosis by Ultrasound Image Deep Learning Model.
Zhang X; Li H; Wang C; Cheng W; Zhu Y; Li D; Jing H; Li S; Hou J; Li J; Li Y; Zhao Y; Mo H; Pang D
Front Oncol; 2021; 11():623506. PubMed ID: 33747937
[No Abstract] [Full Text] [Related]
19. A deep learning-based diagnostic pattern for ultrasound breast imaging: can it reduce unnecessary biopsy?
Zhu YC; Sheng JG; Deng SH; Jiang Q; Guo J
Gland Surg; 2022 Sep; 11(9):1529-1537. PubMed ID: 36221270
[TBL] [Abstract][Full Text] [Related]
20. CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists.
Kim H; Lee D; Cho WS; Lee JC; Goo JM; Kim HC; Park CM
Eur Radiol; 2020 Jun; 30(6):3295-3305. PubMed ID: 32055949
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
