167 related articles for article (PubMed ID: 36849997)
1. Identification of gene profiles related to the development of oral cancer using a deep learning technique.
Tapak L; Ghasemi MK; Afshar S; Mahjub H; Soltanian A; Khotanlou H
BMC Med Genomics; 2023 Feb; 16(1):35. PubMed ID: 36849997
[TBL] [Abstract][Full Text] [Related]
2. Uncovering the prognostic gene signatures for the improvement of risk stratification in cancers by using deep learning algorithm coupled with wavelet transform.
Zhao Y; Zhou Y; Liu Y; Hao Y; Li M; Pu X; Li C; Wen Z
BMC Bioinformatics; 2020 May; 21(1):195. PubMed ID: 32429941
[TBL] [Abstract][Full Text] [Related]
3. Deep learning-based pathology image analysis predicts cancer progression risk in patients with oral leukoplakia.
Zhang X; Gleber-Netto FO; Wang S; Martins-Chaves RR; Gomez RS; Vigneswaran N; Sarkar A; William WN; Papadimitrakopoulou V; Williams M; Bell D; Palsgrove D; Bishop J; Heymach JV; Gillenwater AM; Myers JN; Ferrarotto R; Lippman SM; Pickering CR; Xiao G
Cancer Med; 2023 Mar; 12(6):7508-7518. PubMed ID: 36721313
[TBL] [Abstract][Full Text] [Related]
4. Identification of latent biomarkers in connection with progression and prognosis in oral cancer by comprehensive bioinformatics analysis.
Reyimu A; Chen Y; Song X; Zhou W; Dai J; Jiang F
World J Surg Oncol; 2021 Aug; 19(1):240. PubMed ID: 34384424
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. An Unsupervised Deep Learning-Based Model Using Multiomics Data to Predict Prognosis of Patients with Stomach Adenocarcinoma.
Chen S; Zang Y; Xu B; Lu B; Ma R; Miao P; Chen B
Comput Math Methods Med; 2022; 2022():5844846. PubMed ID: 36339684
[TBL] [Abstract][Full Text] [Related]
7. Deep multiple instance learning versus conventional deep single instance learning for interpretable oral cancer detection.
Koriakina N; Sladoje N; Bašić V; Lindblad J
PLoS One; 2024; 19(4):e0302169. PubMed ID: 38687694
[TBL] [Abstract][Full Text] [Related]
8. Gene expression profiling predicts the development of oral cancer.
Saintigny P; Zhang L; Fan YH; El-Naggar AK; Papadimitrakopoulou VA; Feng L; Lee JJ; Kim ES; Ki Hong W; Mao L
Cancer Prev Res (Phila); 2011 Feb; 4(2):218-29. PubMed ID: 21292635
[TBL] [Abstract][Full Text] [Related]
9. Multi-Run Concrete Autoencoder to Identify Prognostic lncRNAs for 12 Cancers.
Al Mamun A; Tanvir RB; Sobhan M; Mathee K; Narasimhan G; Holt GE; Mondal AM
Int J Mol Sci; 2021 Nov; 22(21):. PubMed ID: 34769351
[TBL] [Abstract][Full Text] [Related]
10. Survival outcome prediction in cervical cancer: Cox models vs deep-learning model.
Matsuo K; Purushotham S; Jiang B; Mandelbaum RS; Takiuchi T; Liu Y; Roman LD
Am J Obstet Gynecol; 2019 Apr; 220(4):381.e1-381.e14. PubMed ID: 30582927
[TBL] [Abstract][Full Text] [Related]
11. The Effectiveness of Artificial Intelligence in Detection of Oral Cancer.
Al-Rawi N; Sultan A; Rajai B; Shuaeeb H; Alnajjar M; Alketbi M; Mohammad Y; Shetty SR; Mashrah MA
Int Dent J; 2022 Aug; 72(4):436-447. PubMed ID: 35581039
[TBL] [Abstract][Full Text] [Related]
12. Novel deep learning-based solution for identification of prognostic subgroups in liver cancer (Hepatocellular carcinoma).
Owens AR; McInerney CE; Prise KM; McArt DG; Jurek-Loughrey A
BMC Bioinformatics; 2021 Nov; 22(1):563. PubMed ID: 34819028
[TBL] [Abstract][Full Text] [Related]
13. Inferring Potential CircRNA-Disease Associations via Deep Autoencoder-Based Classification.
Deepthi K; Jereesh AS
Mol Diagn Ther; 2021 Jan; 25(1):87-97. PubMed ID: 33156515
[TBL] [Abstract][Full Text] [Related]
14. Machine learning and bioinformatics models to identify gene expression patterns of ovarian cancer associated with disease progression and mortality.
Hossain MA; Saiful Islam SM; Quinn JMW; Huq F; Moni MA
J Biomed Inform; 2019 Dec; 100():103313. PubMed ID: 31655274
[TBL] [Abstract][Full Text] [Related]
15. Gene Expression Clustering and Selected Head and Neck Cancer Gene Signatures Highlight Risk Probability Differences in Oral Premalignant Lesions.
Carenzo A; Serafini MS; Roca E; Paderno A; Mattavelli D; Romani C; Saintigny P; Koljenović S; Licitra L; De Cecco L; Bossi P
Cells; 2020 Aug; 9(8):. PubMed ID: 32756466
[TBL] [Abstract][Full Text] [Related]
16. Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations.
Huang Z; Johnson TS; Han Z; Helm B; Cao S; Zhang C; Salama P; Rizkalla M; Yu CY; Cheng J; Xiang S; Zhan X; Zhang J; Huang K
BMC Med Genomics; 2020 Apr; 13(Suppl 5):41. PubMed ID: 32241264
[TBL] [Abstract][Full Text] [Related]
17. A novel risk score system for assessment of ovarian cancer based on co-expression network analysis and expression level of five lncRNAs.
Zhao Q; Fan C
BMC Med Genet; 2019 Jun; 20(1):103. PubMed ID: 31182053
[TBL] [Abstract][Full Text] [Related]
18. Identification and validation of a seven m6A-related lncRNAs signature predicting prognosis of ovarian cancer.
Song Y; Qu H
BMC Cancer; 2022 Jun; 22(1):633. PubMed ID: 35676619
[TBL] [Abstract][Full Text] [Related]
19. Inferring novel genes related to oral cancer with a network embedding method and one-class learning algorithms.
Chen L; Zhang YH; Huang G; Pan X; Huang T; Cai YD
Gene Ther; 2019 Dec; 26(12):465-478. PubMed ID: 31455874
[TBL] [Abstract][Full Text] [Related]
20. Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models.
Jalali-Najafabadi F; Stadler M; Dand N; Jadon D; Soomro M; Ho P; Marzo-Ortega H; Helliwell P; Korendowych E; Simpson MA; Packham J; Smith CH; Barker JN; McHugh N; Warren RB; Barton A; Bowes J; ;
Sci Rep; 2021 Dec; 11(1):23335. PubMed ID: 34857774
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
