120 related articles for article (PubMed ID: 38159398)
1. Prediction of viral pneumonia based on machine learning models analyzing pulmonary inflammation index scores.
Wang Y; Liu ZL; Yang H; Li R; Liao SJ; Huang Y; Peng MH; Liu X; Si GY; He QZ; Zhang Y
Comput Biol Med; 2024 Feb; 169():107905. PubMed ID: 38159398
[TBL] [Abstract][Full Text] [Related]
2. Using a machine learning-based risk prediction model to analyze the coronary artery calcification score and predict coronary heart disease and risk assessment.
Huang Y; Ren Y; Yang H; Ding Y; Liu Y; Yang Y; Mao A; Yang T; Wang Y; Xiao F; He Q; Zhang Y
Comput Biol Med; 2022 Dec; 151(Pt B):106297. PubMed ID: 36435054
[TBL] [Abstract][Full Text] [Related]
3. Postoperative delirium prediction after cardiac surgery using machine learning models.
Yang T; Yang H; Liu Y; Liu X; Ding YJ; Li R; Mao AQ; Huang Y; Li XL; Zhang Y; Yu FX
Comput Biol Med; 2024 Feb; 169():107818. PubMed ID: 38134752
[TBL] [Abstract][Full Text] [Related]
4. Basing on the machine learning model to analyse the coronary calcification score and the coronary flow reserve score to evaluate the degree of coronary artery stenosis.
Zhang Y; Liu P; Tang LJ; Lin PM; Li R; Luo HR; Luo P
Comput Biol Med; 2023 Sep; 163():107130. PubMed ID: 37329614
[TBL] [Abstract][Full Text] [Related]
5. [Construction of a predictive model for in-hospital mortality of sepsis patients in intensive care unit based on machine learning].
Zhu M; Hu C; He Y; Qian Y; Tang S; Hu Q; Hao C
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Jul; 35(7):696-701. PubMed ID: 37545445
[TBL] [Abstract][Full Text] [Related]
6. Comparing machine learning algorithms to predict COVID‑19 mortality using a dataset including chest computed tomography severity score data.
Zakariaee SS; Naderi N; Ebrahimi M; Kazemi-Arpanahi H
Sci Rep; 2023 Jul; 13(1):11343. PubMed ID: 37443373
[TBL] [Abstract][Full Text] [Related]
7. Can machine learning predict pharmacotherapy outcomes? An application study in osteoporosis.
Lin YT; Chu CY; Hung KS; Lu CH; Bednarczyk EM; Chen HY
Comput Methods Programs Biomed; 2022 Oct; 225():107028. PubMed ID: 35930862
[TBL] [Abstract][Full Text] [Related]
8. Mapping the spatial distribution of the dengue vector
Rahman MS; Pientong C; Zafar S; Ekalaksananan T; Paul RE; Haque U; Rocklöv J; Overgaard HJ
One Health; 2021 Dec; 13():100358. PubMed ID: 34934797
[TBL] [Abstract][Full Text] [Related]
9. Machine learning models for predicting critical illness risk in hospitalized patients with COVID-19 pneumonia.
Liu Q; Pang B; Li H; Zhang B; Liu Y; Lai L; Le W; Li J; Xia T; Zhang X; Ou C; Ma J; Li S; Guo X; Zhang S; Zhang Q; Jiang M; Zeng Q
J Thorac Dis; 2021 Feb; 13(2):1215-1229. PubMed ID: 33717594
[TBL] [Abstract][Full Text] [Related]
10. Application of machine learning model in predicting the likelihood of blood transfusion after hip fracture surgery.
Chen X; Pan J; Li Y; Tang R
Aging Clin Exp Res; 2023 Nov; 35(11):2643-2656. PubMed ID: 37733228
[TBL] [Abstract][Full Text] [Related]
11. Differentiating novel coronavirus pneumonia from general pneumonia based on machine learning.
Liu C; Wang X; Liu C; Sun Q; Peng W
Biomed Eng Online; 2020 Aug; 19(1):66. PubMed ID: 32814568
[TBL] [Abstract][Full Text] [Related]
12. A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.
Wang J; Chen H; Wang H; Liu W; Peng D; Zhao Q; Xiao M
J Med Internet Res; 2023 Apr; 25():e43815. PubMed ID: 37023416
[TBL] [Abstract][Full Text] [Related]
13. Predicting omicron pneumonia severity and outcome: a single-center study in Hangzhou, China.
Xu J; Cao Z; Miao C; Zhang M; Xu X
Front Med (Lausanne); 2023; 10():1192376. PubMed ID: 37305146
[TBL] [Abstract][Full Text] [Related]
14. Development and performance assessment of novel machine learning models to predict pneumonia after liver transplantation.
Chen C; Yang D; Gao S; Zhang Y; Chen L; Wang B; Mo Z; Yang Y; Hei Z; Zhou S
Respir Res; 2021 Mar; 22(1):94. PubMed ID: 33789673
[TBL] [Abstract][Full Text] [Related]
15. Joint modeling strategy for using electronic medical records data to build machine learning models: an example of intracerebral hemorrhage.
Tang J; Wang X; Wan H; Lin C; Shao Z; Chang Y; Wang H; Wu Y; Zhang T; Du Y
BMC Med Inform Decis Mak; 2022 Oct; 22(1):278. PubMed ID: 36284327
[TBL] [Abstract][Full Text] [Related]
16. Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.
Li K; Shi Q; Liu S; Xie Y; Liu J
Medicine (Baltimore); 2021 May; 100(19):e25813. PubMed ID: 34106618
[TBL] [Abstract][Full Text] [Related]
17. Prediction of postoperative complications after oesophagectomy using machine-learning methods.
Jung JO; Pisula JI; Bozek K; Popp F; Fuchs HF; Schröder W; Bruns CJ; Schmidt T
Br J Surg; 2023 Sep; 110(10):1361-1366. PubMed ID: 37343072
[TBL] [Abstract][Full Text] [Related]
18. Comparison of Radiomic Models Based on Different Machine Learning Methods for Predicting Intracerebral Hemorrhage Expansion.
Duan C; Liu F; Gao S; Zhao J; Niu L; Li N; Liu S; Wang G; Zhou X; Ren Y; Xu W; Liu X
Clin Neuroradiol; 2022 Mar; 32(1):215-223. PubMed ID: 34156513
[TBL] [Abstract][Full Text] [Related]
19. Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics.
Moradi Khaniabadi P; Bouchareb Y; Al-Dhuhli H; Shiri I; Al-Kindi F; Moradi Khaniabadi B; Zaidi H; Rahmim A
Comput Biol Med; 2022 Nov; 150():106165. PubMed ID: 36215849
[TBL] [Abstract][Full Text] [Related]
20. Development and internal validation of a machine-learning-developed model for predicting 1-year mortality after fragility hip fracture.
Kitcharanant N; Chotiyarnwong P; Tanphiriyakun T; Vanitcharoenkul E; Mahaisavariya C; Boonyaprapa W; Unnanuntana A
BMC Geriatr; 2022 May; 22(1):451. PubMed ID: 35610589
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
