185 related articles for article (PubMed ID: 36072469)
1. Application of Deep Learning on the Prognosis of Cutaneous Melanoma Based on Full Scan Pathology Images.
Li A; Li X; Li W; Yu X; Qi M; Li D
Biomed Res Int; 2022; 2022():4864485. PubMed ID: 36072469
[TBL] [Abstract][Full Text] [Related]
2. A deep bag-of-features model for the classification of melanomas in dermoscopy images.
Sabbaghi S; Aldeen M; Garnavi R
Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():1369-1372. PubMed ID: 28268580
[TBL] [Abstract][Full Text] [Related]
3. Predicting cutaneous malignant melanoma patients' survival using deep learning: a retrospective cohort study.
Cai S; Li W; Deng C; Tang Q; Zhou Z
J Cancer Res Clin Oncol; 2023 Dec; 149(19):17103-17113. PubMed ID: 37755576
[TBL] [Abstract][Full Text] [Related]
4. Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM).
R D S; A S
Asian Pac J Cancer Prev; 2019 May; 20(5):1555-1561. PubMed ID: 31128062
[TBL] [Abstract][Full Text] [Related]
5. A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest x-ray images.
Hu Z; Yang Z; Lafata KJ; Yin FF; Wang C
Med Phys; 2022 May; 49(5):3213-3222. PubMed ID: 35263458
[TBL] [Abstract][Full Text] [Related]
6. Fusing fine-tuned deep features for skin lesion classification.
Mahbod A; Schaefer G; Ellinger I; Ecker R; Pitiot A; Wang C
Comput Med Imaging Graph; 2019 Jan; 71():19-29. PubMed ID: 30458354
[TBL] [Abstract][Full Text] [Related]
7. Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.
Marchetti MA; Liopyris K; Dusza SW; Codella NCF; Gutman DA; Helba B; Kalloo A; Halpern AC;
J Am Acad Dermatol; 2020 Mar; 82(3):622-627. PubMed ID: 31306724
[TBL] [Abstract][Full Text] [Related]
8. Deep learning-level melanoma detection by interpretable machine learning and imaging biomarker cues.
Gareau DS; Browning J; Correa Da Rosa J; Suarez-Farinas M; Lish S; Zong AM; Firester B; Vrattos C; Renert-Yuval Y; Gamboa M; Vallone MG; Barragán-Estudillo ZF; Tamez-Peña AL; Montoya J; Jesús-Silva MA; Carrera C; Malvehy J; Puig S; Marghoob A; Carucci JA; Krueger JG
J Biomed Opt; 2020 Nov; 25(11):. PubMed ID: 33247560
[TBL] [Abstract][Full Text] [Related]
9. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.
Haenssle HA; Fink C; Schneiderbauer R; Toberer F; Buhl T; Blum A; Kalloo A; Hassen ABH; Thomas L; Enk A; Uhlmann L; ; Alt C; Arenbergerova M; Bakos R; Baltzer A; Bertlich I; Blum A; Bokor-Billmann T; Bowling J; Braghiroli N; Braun R; Buder-Bakhaya K; Buhl T; Cabo H; Cabrijan L; Cevic N; Classen A; Deltgen D; Fink C; Georgieva I; Hakim-Meibodi LE; Hanner S; Hartmann F; Hartmann J; Haus G; Hoxha E; Karls R; Koga H; Kreusch J; Lallas A; Majenka P; Marghoob A; Massone C; Mekokishvili L; Mestel D; Meyer V; Neuberger A; Nielsen K; Oliviero M; Pampena R; Paoli J; Pawlik E; Rao B; Rendon A; Russo T; Sadek A; Samhaber K; Schneiderbauer R; Schweizer A; Toberer F; Trennheuser L; Vlahova L; Wald A; Winkler J; Wölbing P; Zalaudek I
Ann Oncol; 2018 Aug; 29(8):1836-1842. PubMed ID: 29846502
[TBL] [Abstract][Full Text] [Related]
10. Exploring and validating the prognostic value of pathomics signatures and genomics in patients with cutaneous melanoma based on bioinformatics and deep learning.
Li X; Yu X; Tian D; Liu Y; Li D
Med Phys; 2023 Nov; 50(11):7049-7059. PubMed ID: 37722701
[TBL] [Abstract][Full Text] [Related]
11. Skin lesion classification with ensembles of deep convolutional neural networks.
Harangi B
J Biomed Inform; 2018 Oct; 86():25-32. PubMed ID: 30103029
[TBL] [Abstract][Full Text] [Related]
12. Bioinformatic and Machine Learning Applications in Melanoma Risk Assessment and Prognosis: A Literature Review.
Ma EZ; Hoegler KM; Zhou AE
Genes (Basel); 2021 Oct; 12(11):. PubMed ID: 34828357
[TBL] [Abstract][Full Text] [Related]
13. Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images.
Marchetti MA; Codella NCF; Dusza SW; Gutman DA; Helba B; Kalloo A; Mishra N; Carrera C; Celebi ME; DeFazio JL; Jaimes N; Marghoob AA; Quigley E; Scope A; Yélamos O; Halpern AC;
J Am Acad Dermatol; 2018 Feb; 78(2):270-277.e1. PubMed ID: 28969863
[TBL] [Abstract][Full Text] [Related]
14. Melanoma Recognition in Dermoscopy Images via Aggregated Deep Convolutional Features.
Yu Z; Jiang X; Zhou F; Qin J; Ni D; Chen S; Lei B; Wang T
IEEE Trans Biomed Eng; 2019 Apr; 66(4):1006-1016. PubMed ID: 30130171
[TBL] [Abstract][Full Text] [Related]
15. Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition.
Winkler JK; Sies K; Fink C; Toberer F; Enk A; Abassi MS; Fuchs T; Haenssle HA
Eur J Cancer; 2021 Mar; 145():146-154. PubMed ID: 33465706
[TBL] [Abstract][Full Text] [Related]
16. Recent Advances in Melanoma Diagnosis and Prognosis Using Machine Learning Methods.
Grossarth S; Mosley D; Madden C; Ike J; Smith I; Huo Y; Wheless L
Curr Oncol Rep; 2023 Jun; 25(6):635-645. PubMed ID: 37000340
[TBL] [Abstract][Full Text] [Related]
17. Novel Approaches for Diagnosing Melanoma Skin Lesions Through Supervised and Deep Learning Algorithms.
Premaladha J; Ravichandran KS
J Med Syst; 2016 Apr; 40(4):96. PubMed ID: 26872778
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning Approaches Towards Skin Lesion Segmentation and Classification from Dermoscopic Images - A Review.
Baig R; Bibi M; Hamid A; Kausar S; Khalid S
Curr Med Imaging; 2020; 16(5):513-533. PubMed ID: 32484086
[TBL] [Abstract][Full Text] [Related]
19. Combining handcrafted features with latent variables in machine learning for prediction of radiation-induced lung damage.
Cui S; Luo Y; Tseng HH; Ten Haken RK; El Naqa I
Med Phys; 2019 May; 46(5):2497-2511. PubMed ID: 30891794
[TBL] [Abstract][Full Text] [Related]
20. A deep learning model based on whole slide images to predict disease-free survival in cutaneous melanoma patients.
Comes MC; Fucci L; Mele F; Bove S; Cristofaro C; De Risi I; Fanizzi A; Milella M; Strippoli S; Zito A; Guida M; Massafra R
Sci Rep; 2022 Nov; 12(1):20366. PubMed ID: 36437296
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
