241 related articles for article (PubMed ID: 36236325)
1. Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers.
Hassan CAU; Iqbal J; Irfan R; Hussain S; Algarni AD; Bukhari SSH; Alturki N; Ullah SS
Sensors (Basel); 2022 Sep; 22(19):. PubMed ID: 36236325
[TBL] [Abstract][Full Text] [Related]
2. Machine Learning Hybrid Model for the Prediction of Chronic Kidney Disease.
Khalid H; Khan A; Zahid Khan M; Mehmood G; Shuaib Qureshi M
Comput Intell Neurosci; 2023; 2023():9266889. PubMed ID: 36959840
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Exploring the use of association rules in random forest for predicting heart disease.
Barry KA; Manzali Y; Flouchi R; Balouki Y; Chelhi K; Elfar M
Comput Methods Biomech Biomed Engin; 2024 Mar; 27(3):338-346. PubMed ID: 36877167
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. Heart disease prediction using supervised machine learning algorithms: Performance analysis and comparison.
Ali MM; Paul BK; Ahmed K; Bui FM; Quinn JMW; Moni MA
Comput Biol Med; 2021 Sep; 136():104672. PubMed ID: 34315030
[TBL] [Abstract][Full Text] [Related]
8. Breast cancer prediction with transcriptome profiling using feature selection and machine learning methods.
Taghizadeh E; Heydarheydari S; Saberi A; JafarpoorNesheli S; Rezaeijo SM
BMC Bioinformatics; 2022 Oct; 23(1):410. PubMed ID: 36183055
[TBL] [Abstract][Full Text] [Related]
9. Application of machine learning classifiers to X-ray diffraction imaging with medically relevant phantoms.
Stryker S; Kapadia AJ; Greenberg JA
Med Phys; 2022 Jan; 49(1):532-546. PubMed ID: 34799852
[TBL] [Abstract][Full Text] [Related]
10. Survival prediction among heart patients using machine learning techniques.
Almazroi AA
Math Biosci Eng; 2022 Jan; 19(1):134-145. PubMed ID: 34902984
[TBL] [Abstract][Full Text] [Related]
11. Precision healthcare: A deep dive into machine learning algorithms and feature selection strategies for accurate heart disease prediction.
Islam MA; Majumder MZH; Miah MS; Jannaty S
Comput Biol Med; 2024 Jun; 176():108432. PubMed ID: 38744014
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Predicting Chronic Kidney Disease Using Hybrid Machine Learning Based on Apache Spark.
Abdel-Fattah MA; Othman NA; Goher N
Comput Intell Neurosci; 2022; 2022():9898831. PubMed ID: 35251161
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Prevalence and Early Prediction of Diabetes Using Machine Learning in North Kashmir: A Case Study of District Bandipora.
Bhat SS; Selvam V; Ansari GA; Ansari MD; Rahman MH
Comput Intell Neurosci; 2022; 2022():2789760. PubMed ID: 36238678
[TBL] [Abstract][Full Text] [Related]
16. Human Locomotion Classification for Different Terrains Using Machine Learning Techniques.
Negi S; Negi PCBS; Sharma S; Sharma N
Crit Rev Biomed Eng; 2020; 48(4):199-209. PubMed ID: 33463957
[TBL] [Abstract][Full Text] [Related]
17. Prediction of coronary heart disease in gout patients using machine learning models.
Jiang L; Chen S; Wu Y; Zhou D; Duan L
Math Biosci Eng; 2023 Jan; 20(3):4574-4591. PubMed ID: 36896513
[TBL] [Abstract][Full Text] [Related]
18. KFPredict: An ensemble learning prediction framework for diabetes based on fusion of key features.
Qi H; Song X; Liu S; Zhang Y; Wong KKL
Comput Methods Programs Biomed; 2023 Apr; 231():107378. PubMed ID: 36731312
[TBL] [Abstract][Full Text] [Related]
19. A Novel Approach for Feature Selection and Classification of Diabetes Mellitus: Machine Learning Methods.
Saxena R; Sharma SK; Gupta M; Sampada GC
Comput Intell Neurosci; 2022; 2022():3820360. PubMed ID: 35463255
[TBL] [Abstract][Full Text] [Related]
20. Incremental Ant-Miner Classifier for Online Big Data Analytics.
Al-Dawsari A; Al-Turaiki I; Kurdi H
Sensors (Basel); 2022 Mar; 22(6):. PubMed ID: 35336394
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
