669 related articles for article (PubMed ID: 30902088)
1. Predicting factors for survival of breast cancer patients using machine learning techniques.
Ganggayah MD; Taib NA; Har YC; Lio P; Dhillon SK
BMC Med Inform Decis Mak; 2019 Mar; 19(1):48. PubMed ID: 30902088
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Predicting Characteristics Associated with Breast Cancer Survival Using Multiple Machine Learning Approaches.
Haque MN; Tazin T; Khan MM; Faisal S; Ibraheem SM; Algethami H; Almalki FA
Comput Math Methods Med; 2022; 2022():1249692. PubMed ID: 35509861
[TBL] [Abstract][Full Text] [Related]
4. Machine Learning and Deep Learning Approaches in Breast Cancer Survival Prediction Using Clinical Data.
Kalafi EY; Nor NAM; Taib NA; Ganggayah MD; Town C; Dhillon SK
Folia Biol (Praha); 2019; 65(5-6):212-220. PubMed ID: 32362304
[TBL] [Abstract][Full Text] [Related]
5. Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers.
Deist TM; Dankers FJWM; Valdes G; Wijsman R; Hsu IC; Oberije C; Lustberg T; van Soest J; Hoebers F; Jochems A; El Naqa I; Wee L; Morin O; Raleigh DR; Bots W; Kaanders JH; Belderbos J; Kwint M; Solberg T; Monshouwer R; Bussink J; Dekker A; Lambin P
Med Phys; 2018 Jul; 45(7):3449-3459. PubMed ID: 29763967
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Personal Health Information Inference Using Machine Learning on RNA Expression Data from Patients With Cancer: Algorithm Validation Study.
Kweon S; Lee JH; Lee Y; Park YR
J Med Internet Res; 2020 Aug; 22(8):e18387. PubMed ID: 32773372
[TBL] [Abstract][Full Text] [Related]
8. Breast Tumor Detection Using Robust and Efficient Machine Learning and Convolutional Neural Network Approaches.
Khan MM; Tazin T; Zunaid Hussain M; Mostakim M; Rehman T; Singh S; Gupta V; Alomeir O
Comput Intell Neurosci; 2022; 2022():6333573. PubMed ID: 35712068
[TBL] [Abstract][Full Text] [Related]
9. Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.
Shirwaikar RD; Acharya U D; Makkithaya K; M S; Srivastava S; Lewis U LES
Artif Intell Med; 2019 Jul; 98():59-76. PubMed ID: 31521253
[TBL] [Abstract][Full Text] [Related]
10. Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer.
Alabi RO; Elmusrati M; Sawazaki-Calone I; Kowalski LP; Haglund C; Coletta RD; Mäkitie AA; Salo T; Almangush A; Leivo I
Int J Med Inform; 2020 Apr; 136():104068. PubMed ID: 31923822
[TBL] [Abstract][Full Text] [Related]
11. Machine learning to predict the occurrence of bisphosphonate-related osteonecrosis of the jaw associated with dental extraction: A preliminary report.
Kim DW; Kim H; Nam W; Kim HJ; Cha IH
Bone; 2018 Nov; 116():207-214. PubMed ID: 29698784
[TBL] [Abstract][Full Text] [Related]
12. Construction the model on the breast cancer survival analysis use support vector machine, logistic regression and decision tree.
Chao CM; Yu YW; Cheng BW; Kuo YL
J Med Syst; 2014 Oct; 38(10):106. PubMed ID: 25119239
[TBL] [Abstract][Full Text] [Related]
13. Prevalence and predicting factors of perceived stress among Bangladeshi university students using machine learning algorithms.
Rois R; Ray M; Rahman A; Roy SK
J Health Popul Nutr; 2021 Nov; 40(1):50. PubMed ID: 34838133
[TBL] [Abstract][Full Text] [Related]
14. Predicting breast cancer survivability: a comparison of three data mining methods.
Delen D; Walker G; Kadam A
Artif Intell Med; 2005 Jun; 34(2):113-27. PubMed ID: 15894176
[TBL] [Abstract][Full Text] [Related]
15. Diagnosis of urinary tract infection based on artificial intelligence methods.
Ozkan IA; Koklu M; Sert IU
Comput Methods Programs Biomed; 2018 Nov; 166():51-59. PubMed ID: 30415718
[TBL] [Abstract][Full Text] [Related]
16. Reviewing ensemble classification methods in breast cancer.
Hosni M; Abnane I; Idri A; Carrillo de Gea JM; Fernández Alemán JL
Comput Methods Programs Biomed; 2019 Aug; 177():89-112. PubMed ID: 31319964
[TBL] [Abstract][Full Text] [Related]
17. Predicting breast cancer-specific survival in metaplastic breast cancer patients using machine learning algorithms.
Feng Y; McGuire N; Walton A; ; Fox S; Papa A; Lakhani SR; McCart Reed AE
J Pathol Inform; 2023; 14():100329. PubMed ID: 37664452
[TBL] [Abstract][Full Text] [Related]
18. Comparison of Classification Success Rates of Different Machine Learning Algorithms in the Diagnosis of Breast Cancer.
Ozcan I; Aydin H; Cetinkaya A
Asian Pac J Cancer Prev; 2022 Oct; 23(10):3287-3297. PubMed ID: 36308351
[TBL] [Abstract][Full Text] [Related]
19. Patient classification and outcome prediction in IgA nephropathy.
Diciolla M; Binetti G; Di Noia T; Pesce F; Schena FP; Vågane AM; Bjørneklett R; Suzuki H; Tomino Y; Naso D
Comput Biol Med; 2015 Nov; 66():278-86. PubMed ID: 26453758
[TBL] [Abstract][Full Text] [Related]
20. Stage-specific predictive models for breast cancer survivability.
Kate RJ; Nadig R
Int J Med Inform; 2017 Jan; 97():304-311. PubMed ID: 27919388
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]