156 related articles for article (PubMed ID: 38828234)
1. Random forest predictive modeling of prolonged hospital length of stay in elderly hip fracture patients.
Liu H; Xing F; Jiang J; Chen Z; Xiang Z; Duan X
Front Med (Lausanne); 2024; 11():1362153. PubMed ID: 38828234
[TBL] [Abstract][Full Text] [Related]
2. Development and external validation of a predictive model for prolonged length of hospital stay in elderly patients undergoing lumbar fusion surgery: comparison of three predictive models.
Wang SK; Wang P; Li ZE; Li XY; Kong C; Zhang ST; Lu SB
Eur Spine J; 2024 Mar; 33(3):1044-1054. PubMed ID: 38291294
[TBL] [Abstract][Full Text] [Related]
3. Machine learning-based prediction of hospital prolonged length of stay admission at emergency department: a Gradient Boosting algorithm analysis.
Zeleke AJ; Palumbo P; Tubertini P; Miglio R; Chiari L
Front Artif Intell; 2023; 6():1179226. PubMed ID: 37588696
[TBL] [Abstract][Full Text] [Related]
4. Predicting Prolonged Length of Hospital Stay for Peritoneal Dialysis-Treated Patients Using Stacked Generalization: Model Development and Validation Study.
Kong G; Wu J; Chu H; Yang C; Lin Y; Lin K; Shi Y; Wang H; Zhang L
JMIR Med Inform; 2021 May; 9(5):e17886. PubMed ID: 34009135
[TBL] [Abstract][Full Text] [Related]
5. Application of machine learning models on predicting the length of hospital stay in fragility fracture patients.
Lai CH; Mok PK; Chau WW; Law SW
BMC Med Inform Decis Mak; 2024 Jan; 24(1):26. PubMed ID: 38291406
[TBL] [Abstract][Full Text] [Related]
6. A New Random Forest Algorithm-Based Prediction Model of Post-operative Mortality in Geriatric Patients With Hip Fractures.
Xing F; Luo R; Liu M; Zhou Z; Xiang Z; Duan X
Front Med (Lausanne); 2022; 9():829977. PubMed ID: 35646950
[TBL] [Abstract][Full Text] [Related]
7. Development and validation of a novel nomogram to predict the risk of the prolonged postoperative length of stay for lumbar spinal stenosis patients.
Yasin P; Cai X; Mardan M; Xu T; Abulizi Y; Aimaiti A; Yang H; Sheng W; Mamat M
BMC Musculoskelet Disord; 2023 Sep; 24(1):703. PubMed ID: 37660009
[TBL] [Abstract][Full Text] [Related]
8. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
Anderson AB; Grazal CF; Balazs GC; Potter BK; Dickens JF; Forsberg JA
Clin Orthop Relat Res; 2020 Jul; 478(7):0-1618. PubMed ID: 32282466
[TBL] [Abstract][Full Text] [Related]
9. Machine learning applications for the prediction of extended length of stay in geriatric hip fracture patients.
Tian CW; Chen XX; Shi L; Zhu HY; Dai GC; Chen H; Rui YF
World J Orthop; 2023 Oct; 14(10):741-754. PubMed ID: 37970626
[TBL] [Abstract][Full Text] [Related]
10. Construction and validation of a risk prediction model for delayed discharge in elderly patients with hip fracture.
Cao H; Yu J; Chang Y; Li Y; Zhou B
BMC Musculoskelet Disord; 2023 Jan; 24(1):66. PubMed ID: 36694160
[TBL] [Abstract][Full Text] [Related]
11. Establishment and validation of an artificial intelligence web application for predicting postoperative in-hospital mortality in patients with hip fracture: a National cohort study of 52,707 cases.
Lei M; Feng T; Chen M; Shen J; Liu J; Chang F; Chen J; Sun X; Mao Z; Li Y; Yin P; Tang P; Zhang L
Int J Surg; 2024 May; ():. PubMed ID: 38752505
[TBL] [Abstract][Full Text] [Related]
12. Predictive characteristics and model development for acute heart failure preceding hip fracture surgery in elderly hypertensive patients: a retrospective machine learning approach.
Yu Q; Fu M; Wang Z; Hou Z
BMC Geriatr; 2024 Mar; 24(1):296. PubMed ID: 38549043
[TBL] [Abstract][Full Text] [Related]
13. Development of a scoring tool for predicting prolonged length of hospital stay in peritoneal dialysis patients through data mining.
Wu J; Kong G; Lin Y; Chu H; Yang C; Shi Y; Wang H; Zhang L
Ann Transl Med; 2020 Nov; 8(21):1437. PubMed ID: 33313182
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Machine-learning prediction for hospital length of stay using a French medico-administrative database.
Jaotombo F; Pauly V; Fond G; Orleans V; Auquier P; Ghattas B; Boyer L
J Mark Access Health Policy; 2023; 11(1):2149318. PubMed ID: 36457821
[TBL] [Abstract][Full Text] [Related]
16. A machine learning-based prediction model pre-operatively for functional recovery after 1-year of hip fracture surgery in older people.
Lin C; Liang Z; Liu J; Sun W
Front Surg; 2023; 10():1160085. PubMed ID: 37351328
[TBL] [Abstract][Full Text] [Related]
17. Development and Validation of a Prognostic Classification Model Predicting Postoperative Adverse Outcomes in Older Surgical Patients Using a Machine Learning Algorithm: Retrospective Observational Network Study.
Choi JY; Yoo S; Song W; Kim S; Baek H; Lee JS; Yoon YS; Yoon S; Lee HY; Kim KI
J Med Internet Res; 2023 Nov; 25():e42259. PubMed ID: 37955965
[TBL] [Abstract][Full Text] [Related]
18. Development and comparison of machine-learning models for predicting prolonged postoperative length of stay in lung cancer patients following video-assisted thoracoscopic surgery.
Zhang G; Liu X; Hu Y; Luo Q; Ruan L; Xie H; Zeng Y
Asia Pac J Oncol Nurs; 2024 Jun; 11(6):100493. PubMed ID: 38808011
[TBL] [Abstract][Full Text] [Related]
19. [Predicting prolonged length of intensive care unit stay
Wu JY; Lin Y; Lin K; Hu YH; Kong GL
Beijing Da Xue Xue Bao Yi Xue Ban; 2021 Dec; 53(6):1163-1170. PubMed ID: 34916699
[TBL] [Abstract][Full Text] [Related]
20. Machine Learning Models Based on a National-Scale Cohort Identify Patients at High Risk for Prolonged Lengths of Stay Following Primary Total Hip Arthroplasty.
Chen TL; Buddhiraju A; Costales TG; Subih MA; Seo HH; Kwon YM
J Arthroplasty; 2023 Oct; 38(10):1967-1972. PubMed ID: 37315634
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]