106 related articles for article (PubMed ID: 38966533)
1. Enhanced cardiovascular disease prediction through self-improved Aquila optimized feature selection in quantum neural network & LSTM model.
Darolia A; Chhillar RS; Alhussein M; Dalal S; Aurangzeb K; Lilhore UK
Front Med (Lausanne); 2024; 11():1414637. PubMed ID: 38966533
[TBL] [Abstract][Full Text] [Related]
2. A hybrid feature weighted attention based deep learning approach for an intrusion detection system using the random forest algorithm.
Hashmi A; Barukab OM; Hamza Osman A
PLoS One; 2024; 19(5):e0302294. PubMed ID: 38781186
[TBL] [Abstract][Full Text] [Related]
3. Support vector machine-based stock market prediction using long short-term memory and convolutional neural network with aquila circle inspired optimization.
Karthick Myilvahanan J; Mohana Sundaram N
Network; 2024 Jun; ():1-36. PubMed ID: 38855971
[TBL] [Abstract][Full Text] [Related]
4. Current-Visit and Next-Visit Prediction for Fatty Liver Disease With a Large-Scale Dataset: Model Development and Performance Comparison.
Wu CT; Chu TW; Jang JR
JMIR Med Inform; 2021 Aug; 9(8):e26398. PubMed ID: 34387552
[TBL] [Abstract][Full Text] [Related]
5. An enhanced and efficient approach for feature selection for chronic human disease prediction: A breast cancer study.
Khanna M; Singh LK; Shrivastava K; Singh R
Heliyon; 2024 Mar; 10(5):e26799. PubMed ID: 38463826
[TBL] [Abstract][Full Text] [Related]
6. Cardiovascular disease incidence prediction by machine learning and statistical techniques: a 16-year cohort study from eastern Mediterranean region.
Mehrabani-Zeinabad K; Feizi A; Sadeghi M; Roohafza H; Talaei M; Sarrafzadegan N
BMC Med Inform Decis Mak; 2023 Apr; 23(1):72. PubMed ID: 37076833
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Enhanced Cardiovascular Disease Prediction Modelling using Machine Learning Techniques: A Focus on CardioVitalnet.
Ejiyi CJ; Qin Z; Nneji GU; Monday HN; Agbesi VK; Ejiyi MB; Ejiyi TU; Bamisile OO
Network; 2024 Apr; ():1-33. PubMed ID: 38626055
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. S-LSTM-ATT: a hybrid deep learning approach with optimized features for emotion recognition in electroencephalogram.
Abgeena A; Garg S
Health Inf Sci Syst; 2023 Dec; 11(1):40. PubMed ID: 37654692
[TBL] [Abstract][Full Text] [Related]
11. Enhanced Evolutionary Feature Selection and Ensemble Method for Cardiovascular Disease Prediction.
Jothi Prakash V; Karthikeyan NK
Interdiscip Sci; 2021 Sep; 13(3):389-412. PubMed ID: 33988832
[TBL] [Abstract][Full Text] [Related]
12. Comparative analysis of supervised learning algorithms for prediction of cardiovascular diseases.
Dou Y; Liu J; Meng W; Zhang Y
Technol Health Care; 2024; 32(S1):241-251. PubMed ID: 38759053
[TBL] [Abstract][Full Text] [Related]
13. Classification of Heart Disease Using MFO Based Neural Network on MRI Images.
K K; N UM; R V
Curr Med Imaging; 2021; 17(9):1114-1127. PubMed ID: 33573572
[TBL] [Abstract][Full Text] [Related]
14. Prediction of diabetes disease using an ensemble of machine learning multi-classifier models.
Abnoosian K; Farnoosh R; Behzadi MH
BMC Bioinformatics; 2023 Sep; 24(1):337. PubMed ID: 37697283
[TBL] [Abstract][Full Text] [Related]
15. Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective.
Olisah CC; Smith L; Smith M
Comput Methods Programs Biomed; 2022 Jun; 220():106773. PubMed ID: 35429810
[TBL] [Abstract][Full Text] [Related]
16. A novel hybrid model based on two-stage data processing and machine learning for forecasting chlorophyll-a concentration in reservoirs.
Yu W; Wang X; Jiang X; Zhao R; Zhao S
Environ Sci Pollut Res Int; 2024 Jan; 31(1):262-279. PubMed ID: 38015396
[TBL] [Abstract][Full Text] [Related]
17. Epileptic Patient Activity Recognition System Using Extreme Learning Machine Method.
Ayman U; Zia MS; Okon OD; Rehman NU; Meraj T; Ragab AE; Rauf HT
Biomedicines; 2023 Mar; 11(3):. PubMed ID: 36979795
[TBL] [Abstract][Full Text] [Related]
18. Optimal path selection and secured data transmission in underwater acoustic sensor networks: LSTM-based energy prediction.
Kaveripakam S; Chinthaginjala R
PLoS One; 2023; 18(9):e0289306. PubMed ID: 37669288
[TBL] [Abstract][Full Text] [Related]
19. New onset delirium prediction using machine learning and long short-term memory (LSTM) in electronic health record.
Liu S; Schlesinger JJ; McCoy AB; Reese TJ; Steitz B; Russo E; Koh B; Wright A
J Am Med Inform Assoc; 2022 Dec; 30(1):120-131. PubMed ID: 36303456
[TBL] [Abstract][Full Text] [Related]
20. Ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices.
Vos G; Trinh K; Sarnyai Z; Rahimi Azghadi M
J Biomed Inform; 2023 Dec; 148():104556. PubMed ID: 38048895
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
