271 related articles for article (PubMed ID: 37507752)
1. Prediction performance of the machine learning model in predicting mortality risk in patients with traumatic brain injuries: a systematic review and meta-analysis.
Wang J; Yin MJ; Wen HC
BMC Med Inform Decis Mak; 2023 Jul; 23(1):142. PubMed ID: 37507752
[TBL] [Abstract][Full Text] [Related]
2. Predictive Value of Machine Learning Models in Postoperative Mortality of Older Adults Patients with Hip Fracture: A Systematic Review and Meta-analysis.
Liu F; Liu C; Tang X; Gong D; Zhu J; Zhang X
Arch Gerontol Geriatr; 2023 Dec; 115():105120. PubMed ID: 37473692
[TBL] [Abstract][Full Text] [Related]
3. Machine learning for the prediction of sepsis-related death: a systematic review and meta-analysis.
Zhang Y; Xu W; Yang P; Zhang A
BMC Med Inform Decis Mak; 2023 Dec; 23(1):283. PubMed ID: 38082381
[TBL] [Abstract][Full Text] [Related]
4. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
[TBL] [Abstract][Full Text] [Related]
5. Comparison of Glasgow Coma Scale and Full Outline of UnResponsiveness score for prediction of in-hospital mortality in traumatic brain injury patients: a systematic review and meta-analysis.
Ahmadi S; Sarveazad A; Babahajian A; Ahmadzadeh K; Yousefifard M
Eur J Trauma Emerg Surg; 2023 Aug; 49(4):1693-1706. PubMed ID: 36152069
[TBL] [Abstract][Full Text] [Related]
6. The predictive value of machine learning for mortality risk in patients with acute coronary syndromes: a systematic review and meta-analysis.
Zhang X; Wang X; Xu L; Liu J; Ren P; Wu H
Eur J Med Res; 2023 Oct; 28(1):451. PubMed ID: 37864271
[TBL] [Abstract][Full Text] [Related]
7. Prediction of in-hospital mortality in patients on mechanical ventilation post traumatic brain injury: machine learning approach.
Abujaber A; Fadlalla A; Gammoh D; Abdelrahman H; Mollazehi M; El-Menyar A
BMC Med Inform Decis Mak; 2020 Dec; 20(1):336. PubMed ID: 33317528
[TBL] [Abstract][Full Text] [Related]
8. The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis.
Li Y; Feng Y; He Q; Ni Z; Hu X; Feng X; Ni M
BMC Infect Dis; 2024 May; 24(1):474. PubMed ID: 38711068
[TBL] [Abstract][Full Text] [Related]
9. Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach.
Abujaber A; Fadlalla A; Gammoh D; Abdelrahman H; Mollazehi M; El-Menyar A
Scand J Trauma Resusc Emerg Med; 2020 May; 28(1):44. PubMed ID: 32460867
[TBL] [Abstract][Full Text] [Related]
10. Predictive value of machine learning for breast cancer recurrence: a systematic review and meta-analysis.
Lu D; Long X; Fu W; Liu B; Zhou X; Sun S
J Cancer Res Clin Oncol; 2023 Sep; 149(12):10659-10674. PubMed ID: 37302114
[TBL] [Abstract][Full Text] [Related]
11. Mortality Prediction in Severe Traumatic Brain Injury Using Traditional and Machine Learning Algorithms.
Wu X; Sun Y; Xu X; Steyerberg EW; Helmrich IRAR; Lecky F; Guo J; Li X; Feng J; Mao Q; Xie G; Maas AIR; Gao G; Jiang J
J Neurotrauma; 2023 Jul; 40(13-14):1366-1375. PubMed ID: 37062757
[No Abstract] [Full Text] [Related]
12. Machine-learning analysis outperforms conventional statistical models and CT classification systems in predicting 6-month outcomes in pediatric patients sustaining traumatic brain injury.
Hale AT; Stonko DP; Brown A; Lim J; Voce DJ; Gannon SR; Le TM; Shannon CN
Neurosurg Focus; 2018 Nov; 45(5):E2. PubMed ID: 30453455
[TBL] [Abstract][Full Text] [Related]
13. Predictive value of machine learning for the severity of acute pancreatitis: A systematic review and meta-analysis.
Qian R; Zhuang J; Xie J; Cheng H; Ou H; Lu X; Ouyang Z
Heliyon; 2024 Apr; 10(8):e29603. PubMed ID: 38655348
[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. Application of machine learning to predict the outcome of pediatric traumatic brain injury.
Tunthanathip T; Oearsakul T
Chin J Traumatol; 2021 Nov; 24(6):350-355. PubMed ID: 34284922
[TBL] [Abstract][Full Text] [Related]
16. Machine learning-based prediction models for pressure injury: A systematic review and meta-analysis.
Pei J; Guo X; Tao H; Wei Y; Zhang H; Ma Y; Han L
Int Wound J; 2023 Dec; 20(10):4328-4339. PubMed ID: 37340520
[TBL] [Abstract][Full Text] [Related]
17. Machine Learning to Predict In-Hospital Morbidity and Mortality after Traumatic Brain Injury.
Matsuo K; Aihara H; Nakai T; Morishita A; Tohma Y; Kohmura E
J Neurotrauma; 2020 Jan; 37(1):202-210. PubMed ID: 31359814
[TBL] [Abstract][Full Text] [Related]
18. The diagnostic and prognostic value of glial fibrillary acidic protein in traumatic brain injury: a systematic review and meta-analysis.
Pei Y; Tang X; Zhang E; Lu K; Xia B; Zhang J; Huang Y; Zhang H; Dong L
Eur J Trauma Emerg Surg; 2023 Jun; 49(3):1235-1246. PubMed ID: 35525877
[TBL] [Abstract][Full Text] [Related]
19. Systemic immune inflammation index and peripheral blood carbon dioxide concentration at admission predict poor prognosis in patients with severe traumatic brain injury.
Chen L; Xia S; Zuo Y; Lin Y; Qiu X; Chen Q; Feng T; Xia X; Shao Q; Wang S
Front Immunol; 2022; 13():1034916. PubMed ID: 36700228
[TBL] [Abstract][Full Text] [Related]
20. An Assessment of the Predictive Performance of Current Machine Learning-Based Breast Cancer Risk Prediction Models: Systematic Review.
Gao Y; Li S; Jin Y; Zhou L; Sun S; Xu X; Li S; Yang H; Zhang Q; Wang Y
JMIR Public Health Surveill; 2022 Dec; 8(12):e35750. PubMed ID: 36426919
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]