543 related articles for article (PubMed ID: 31374261)
1. Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease).
Beunza JJ; Puertas E; García-Ovejero E; Villalba G; Condes E; Koleva G; Hurtado C; Landecho MF
J Biomed Inform; 2019 Sep; 97():103257. PubMed ID: 31374261
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Machine-learning prediction of adolescent alcohol use: a cross-study, cross-cultural validation.
Afzali MH; Sunderland M; Stewart S; Masse B; Seguin J; Newton N; Teesson M; Conrod P
Addiction; 2019 Apr; 114(4):662-671. PubMed ID: 30461117
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Comparison of Supervised Machine Learning Algorithms for Classifying of Home Discharge Possibility in Convalescent Stroke Patients: A Secondary Analysis.
Imura T; Toda H; Iwamoto Y; Inagawa T; Imada N; Tanaka R; Inoue Y; Araki H; Araki O
J Stroke Cerebrovasc Dis; 2021 Oct; 30(10):106011. PubMed ID: 34325274
[TBL] [Abstract][Full Text] [Related]
6. A comparative study on feature selection for a risk prediction model for colorectal cancer.
Cueto-López N; García-Ordás MT; Dávila-Batista V; Moreno V; Aragonés N; Alaiz-Rodríguez R
Comput Methods Programs Biomed; 2019 Aug; 177():219-229. PubMed ID: 31319951
[TBL] [Abstract][Full Text] [Related]
7. Efficient Prediction of Missed Clinical Appointment Using Machine Learning.
Qureshi Z; Maqbool A; Mirza A; Iqbal MZ; Afzal F; Kanubala DD; Rana T; Umair MY; Wakeel A; Shah SK
Comput Math Methods Med; 2021; 2021():2376391. PubMed ID: 34721656
[TBL] [Abstract][Full Text] [Related]
8. Application of supervised machine learning algorithms for classification and prediction of type-2 diabetes disease status in Afar regional state, Northeastern Ethiopia 2021.
Ebrahim OA; Derbew G
Sci Rep; 2023 May; 13(1):7779. PubMed ID: 37179444
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Prediction of Flight Time Deviation for Lithuanian Airports Using Supervised Machine Learning Model.
Stefanovič P; Štrimaitis R; Kurasova O
Comput Intell Neurosci; 2020; 2020():8878681. PubMed ID: 33178261
[TBL] [Abstract][Full Text] [Related]
11. Can machine-learning improve cardiovascular risk prediction using routine clinical data?
Weng SF; Reps J; Kai J; Garibaldi JM; Qureshi N
PLoS One; 2017; 12(4):e0174944. PubMed ID: 28376093
[TBL] [Abstract][Full Text] [Related]
12. Bioactivity Comparison across Multiple Machine Learning Algorithms Using over 5000 Datasets for Drug Discovery.
Lane TR; Foil DH; Minerali E; Urbina F; Zorn KM; Ekins S
Mol Pharm; 2021 Jan; 18(1):403-415. PubMed ID: 33325717
[TBL] [Abstract][Full Text] [Related]
13. Application of supervised machine learning algorithms in the classification of sagittal gait patterns of cerebral palsy children with spastic diplegia.
Zhang Y; Ma Y
Comput Biol Med; 2019 Mar; 106():33-39. PubMed ID: 30665140
[TBL] [Abstract][Full Text] [Related]
14. The predictive effect of different machine learning algorithms for pressure injuries in hospitalized patients: A network meta-analyses.
Qu C; Luo W; Zeng Z; Lin X; Gong X; Wang X; Zhang Y; Li Y
Heliyon; 2022 Nov; 8(11):e11361. PubMed ID: 36387440
[TBL] [Abstract][Full Text] [Related]
15. Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status.
Kocak B; Durmaz ES; Ates E; Sel I; Turgut Gunes S; Kaya OK; Zeynalova A; Kilickesmez O
Eur Radiol; 2020 Feb; 30(2):877-886. PubMed ID: 31691122
[TBL] [Abstract][Full Text] [Related]
16. Comparison of Support Vector Machine, Naïve Bayes and Logistic Regression for Assessing the Necessity for Coronary Angiography.
Golpour P; Ghayour-Mobarhan M; Saki A; Esmaily H; Taghipour A; Tajfard M; Ghazizadeh H; Moohebati M; Ferns GA
Int J Environ Res Public Health; 2020 Sep; 17(18):. PubMed ID: 32899733
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Comparing different supervised machine learning algorithms for disease prediction.
Uddin S; Khan A; Hossain ME; Moni MA
BMC Med Inform Decis Mak; 2019 Dec; 19(1):281. PubMed ID: 31864346
[TBL] [Abstract][Full Text] [Related]
19. Score and Correlation Coefficient-Based Feature Selection for Predicting Heart Failure Diagnosis by Using Machine Learning Algorithms.
Senan EM; Abunadi I; Jadhav ME; Fati SM
Comput Math Methods Med; 2021; 2021():8500314. PubMed ID: 34966445
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
