536 related articles for article (PubMed ID: 30481172)
1. Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study.
Corey KM; Kashyap S; Lorenzi E; Lagoo-Deenadayalan SA; Heller K; Whalen K; Balu S; Heflin MT; McDonald SR; Swaminathan M; Sendak M
PLoS Med; 2018 Nov; 15(11):e1002701. PubMed ID: 30481172
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. A Tool to Estimate Risk of 30-day Mortality and Complications After Hip Fracture Surgery: Accurate Enough for Some but Not All Purposes? A Study From the ACS-NSQIP Database.
Harris AHS; Trickey AW; Eddington HS; Seib CD; Kamal RN; Kuo AC; Ding Q; Giori NJ
Clin Orthop Relat Res; 2022 Dec; 480(12):2335-2346. PubMed ID: 35901441
[TBL] [Abstract][Full Text] [Related]
4. Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform.
Ren Y; Loftus TJ; Datta S; Ruppert MM; Guan Z; Miao S; Shickel B; Feng Z; Giordano C; Upchurch GR; Rashidi P; Ozrazgat-Baslanti T; Bihorac A
JAMA Netw Open; 2022 May; 5(5):e2211973. PubMed ID: 35576007
[TBL] [Abstract][Full Text] [Related]
5. Machine-learning Models Predict 30-Day Mortality, Cardiovascular Complications, and Respiratory Complications After Aseptic Revision Total Joint Arthroplasty.
Abraham VM; Booth G; Geiger P; Balazs GC; Goldman A
Clin Orthop Relat Res; 2022 Nov; 480(11):2137-2145. PubMed ID: 35767804
[TBL] [Abstract][Full Text] [Related]
6. Can Machine-learning Algorithms Predict Early Revision TKA in the Danish Knee Arthroplasty Registry?
El-Galaly A; Grazal C; Kappel A; Nielsen PT; Jensen SL; Forsberg JA
Clin Orthop Relat Res; 2020 Sep; 478(9):2088-2101. PubMed ID: 32667760
[TBL] [Abstract][Full Text] [Related]
7. Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.
Rahimian F; Salimi-Khorshidi G; Payberah AH; Tran J; Ayala Solares R; Raimondi F; Nazarzadeh M; Canoy D; Rahimi K
PLoS Med; 2018 Nov; 15(11):e1002695. PubMed ID: 30458006
[TBL] [Abstract][Full Text] [Related]
8. Development and Validation of a Machine Learning Model to Identify Patients Before Surgery at High Risk for Postoperative Adverse Events.
Mahajan A; Esper S; Oo TH; McKibben J; Garver M; Artman J; Klahre C; Ryan J; Sadhasivam S; Holder-Murray J; Marroquin OC
JAMA Netw Open; 2023 Jul; 6(7):e2322285. PubMed ID: 37418262
[TBL] [Abstract][Full Text] [Related]
9. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.
Taylor RA; Pare JR; Venkatesh AK; Mowafi H; Melnick ER; Fleischman W; Hall MK
Acad Emerg Med; 2016 Mar; 23(3):269-78. PubMed ID: 26679719
[TBL] [Abstract][Full Text] [Related]
10. Postoperative delirium prediction using machine learning models and preoperative electronic health record data.
Bishara A; Chiu C; Whitlock EL; Douglas VC; Lee S; Butte AJ; Leung JM; Donovan AL
BMC Anesthesiol; 2022 Jan; 22(1):8. PubMed ID: 34979919
[TBL] [Abstract][Full Text] [Related]
11. Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study.
Lin H; Long E; Ding X; Diao H; Chen Z; Liu R; Huang J; Cai J; Xu S; Zhang X; Wang D; Chen K; Yu T; Wu D; Zhao X; Liu Z; Wu X; Jiang Y; Yang X; Cui D; Liu W; Zheng Y; Luo L; Wang H; Chan CC; Morgan IG; He M; Liu Y
PLoS Med; 2018 Nov; 15(11):e1002674. PubMed ID: 30399150
[TBL] [Abstract][Full Text] [Related]
12. Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study.
Bonde A; Varadarajan KM; Bonde N; Troelsen A; Muratoglu OK; Malchau H; Yang AD; Alam H; Sillesen M
Lancet Digit Health; 2021 Aug; 3(8):e471-e485. PubMed ID: 34215564
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. The ACS NSQIP Risk Calculator Is a Fair Predictor of Acute Periprosthetic Joint Infection.
Wingert NC; Gotoff J; Parrilla E; Gotoff R; Hou L; Ghanem E
Clin Orthop Relat Res; 2016 Jul; 474(7):1643-8. PubMed ID: 26911971
[TBL] [Abstract][Full Text] [Related]
15. Can Machine Learning Methods Produce Accurate and Easy-to-use Prediction Models of 30-day Complications and Mortality After Knee or Hip Arthroplasty?
Harris AHS; Kuo AC; Weng Y; Trickey AW; Bowe T; Giori NJ
Clin Orthop Relat Res; 2019 Feb; 477(2):452-460. PubMed ID: 30624314
[TBL] [Abstract][Full Text] [Related]
16. Development and Validation of an Electronic Health Record-Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment.
Wong A; Young AT; Liang AS; Gonzales R; Douglas VC; Hadley D
JAMA Netw Open; 2018 Aug; 1(4):e181018. PubMed ID: 30646095
[TBL] [Abstract][Full Text] [Related]
17. Predicting Survival From Large Echocardiography and Electronic Health Record Datasets: Optimization With Machine Learning.
Samad MD; Ulloa A; Wehner GJ; Jing L; Hartzel D; Good CW; Williams BA; Haggerty CM; Fornwalt BK
JACC Cardiovasc Imaging; 2019 Apr; 12(4):681-689. PubMed ID: 29909114
[TBL] [Abstract][Full Text] [Related]
18. Using Machine Learning and Deep Learning Algorithms to Predict Postoperative Outcomes Following Anterior Cervical Discectomy and Fusion.
Khazanchi R; Bajaj A; Shah RM; Chen AR; Reyes SG; Kurapaty SS; Hsu WK; Patel AA; Divi SN
Clin Spine Surg; 2023 Apr; 36(3):143-149. PubMed ID: 36920355
[TBL] [Abstract][Full Text] [Related]
19. Prediction of Prolonged Opioid Use After Surgery in Adolescents: Insights From Machine Learning.
Ward A; Jani T; De Souza E; Scheinker D; Bambos N; Anderson TA
Anesth Analg; 2021 Aug; 133(2):304-313. PubMed ID: 33939656
[TBL] [Abstract][Full Text] [Related]
20. An automated machine learning-based model predicts postoperative mortality using readily-extractable preoperative electronic health record data.
Hill BL; Brown R; Gabel E; Rakocz N; Lee C; Cannesson M; Baldi P; Olde Loohuis L; Johnson R; Jew B; Maoz U; Mahajan A; Sankararaman S; Hofer I; Halperin E
Br J Anaesth; 2019 Dec; 123(6):877-886. PubMed ID: 31627890
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
