100 related articles for article (PubMed ID: 33359319)
1. Logistic regression and machine learning predicted patient mortality from large sets of diagnosis codes comparably.
Cowling TE; Cromwell DA; Bellot A; Sharples LD; van der Meulen J
J Clin Epidemiol; 2021 May; 133():43-52. PubMed ID: 33359319
[TBL] [Abstract][Full Text] [Related]
2. A novel approach selected small sets of diagnosis codes with high prediction performance in large healthcare datasets.
Cowling TE; Cromwell DA; Sharples LD; van der Meulen J
J Clin Epidemiol; 2020 Dec; 128():20-28. PubMed ID: 32781116
[TBL] [Abstract][Full Text] [Related]
3. Comparison of Machine Learning Methods With Traditional Models for Use of Administrative Claims With Electronic Medical Records to Predict Heart Failure Outcomes.
Desai RJ; Wang SV; Vaduganathan M; Evers T; Schneeweiss S
JAMA Netw Open; 2020 Jan; 3(1):e1918962. PubMed ID: 31922560
[TBL] [Abstract][Full Text] [Related]
4. Predictors of 30-Day Mortality Among Dutch Patients Undergoing Colorectal Cancer Surgery, 2011-2016.
van den Bosch T; Warps AK; de Nerée Tot Babberich MPM; Stamm C; Geerts BF; Vermeulen L; Wouters MWJM; Dekker JWT; Tollenaar RAEM; Tanis PJ; Miedema DM;
JAMA Netw Open; 2021 Apr; 4(4):e217737. PubMed ID: 33900400
[TBL] [Abstract][Full Text] [Related]
5. One-year mortality of colorectal cancer patients: development and validation of a prediction model using linked national electronic data.
Cowling TE; Bellot A; Boyle J; Walker K; Kuryba A; Galbraith S; Aggarwal A; Braun M; Sharples LD; van der Meulen J
Br J Cancer; 2020 Nov; 123(10):1474-1480. PubMed ID: 32830202
[TBL] [Abstract][Full Text] [Related]
6. Outcomes After Hip Fracture Surgery Compared With Elective Total Hip Replacement.
Le Manach Y; Collins G; Bhandari M; Bessissow A; Boddaert J; Khiami F; Chaudhry H; De Beer J; Riou B; Landais P; Winemaker M; Boudemaghe T; Devereaux PJ
JAMA; 2015 Sep; 314(11):1159-66. PubMed ID: 26372585
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. ICD-10 adaptations of the Ontario acute myocardial infarction mortality prediction rules performed as well as the original versions.
Vermeulen MJ; Tu JV; Schull MJ
J Clin Epidemiol; 2007 Sep; 60(9):971-4. PubMed ID: 17689814
[TBL] [Abstract][Full Text] [Related]
9. The ICD-10 Charlson Comorbidity Index predicted mortality but not resource utilization following hip fracture.
Toson B; Harvey LA; Close JC
J Clin Epidemiol; 2015 Jan; 68(1):44-51. PubMed ID: 25447352
[TBL] [Abstract][Full Text] [Related]
10. Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data.
Mandair D; Tiwari P; Simon S; Colborn KL; Rosenberg MA
BMC Med Inform Decis Mak; 2020 Oct; 20(1):252. PubMed ID: 33008368
[TBL] [Abstract][Full Text] [Related]
11. Predictors of mortality in older hip fracture inpatients admitted to an orthogeriatric unit in oslo, norway.
Holvik K; Ranhoff AH; Martinsen MI; Solheim LF
J Aging Health; 2010 Dec; 22(8):1114-31. PubMed ID: 20881106
[TBL] [Abstract][Full Text] [Related]
12. Primary care electronic medical records can be used to predict risk and identify potentially modifiable factors for early and late death in adult onset epilepsy.
Hrabok M; Engbers JDT; Wiebe S; Sajobi TT; Subota A; Almohawes A; Federico P; Hanson A; Klein KM; Peedicail J; Pillay N; Singh S; Josephson CB
Epilepsia; 2021 Jan; 62(1):51-60. PubMed ID: 33316095
[TBL] [Abstract][Full Text] [Related]
13. Development and Validation of Machine Learning Models for Prediction of 1-Year Mortality Utilizing Electronic Medical Record Data Available at the End of Hospitalization in Multicondition Patients: a Proof-of-Concept Study.
Sahni N; Simon G; Arora R
J Gen Intern Med; 2018 Jun; 33(6):921-928. PubMed ID: 29383551
[TBL] [Abstract][Full Text] [Related]
14. External validation of ADO, DOSE, COTE and CODEX at predicting death in primary care patients with COPD using standard and machine learning approaches.
Morales DR; Flynn R; Zhang J; Trucco E; Quint JK; Zutis K
Respir Med; 2018 May; 138():150-155. PubMed ID: 29724388
[TBL] [Abstract][Full Text] [Related]
15. Using Machine Learning to Predict Rehabilitation Outcomes in Postacute Hip Fracture Patients.
Shtar G; Rokach L; Shapira B; Nissan R; Hershkovitz A
Arch Phys Med Rehabil; 2021 Mar; 102(3):386-394. PubMed ID: 32949551
[TBL] [Abstract][Full Text] [Related]
16. Bayesian logistic injury severity score: a method for predicting mortality using international classification of disease-9 codes.
Burd RS; Ouyang M; Madigan D
Acad Emerg Med; 2008 May; 15(5):466-75. PubMed ID: 18439203
[TBL] [Abstract][Full Text] [Related]
17. Comorbidity scores for administrative data benefited from adaptation to local coding and diagnostic practices.
Bottle A; Aylin P
J Clin Epidemiol; 2011 Dec; 64(12):1426-33. PubMed ID: 21764557
[TBL] [Abstract][Full Text] [Related]
18. [Risk Prediction Using Routine Data: Development and Validation of Multivariable Models Predicting 30- and 90-day Mortality after Surgical Treatment of Colorectal Cancer].
Crispin A; Strahwald B; Cheney C; Mansmann U
Gesundheitswesen; 2018 Nov; 80(11):963-973. PubMed ID: 29864770
[TBL] [Abstract][Full Text] [Related]
19. Comparing Machine Learning to Regression Methods for Mortality Prediction Using Veterans Affairs Electronic Health Record Clinical Data.
Jing B; Boscardin WJ; Deardorff WJ; Jeon SY; Lee AK; Donovan AL; Lee SJ
Med Care; 2022 Jun; 60(6):470-479. PubMed ID: 35352701
[TBL] [Abstract][Full Text] [Related]
20. Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome - the MADDEC study.
Hernesniemi JA; Mahdiani S; Tynkkynen JA; Lyytikäinen LP; Mishra PP; Lehtimäki T; Eskola M; Nikus K; Antila K; Oksala N
Ann Med; 2019 Mar; 51(2):156-163. PubMed ID: 31030570
[No Abstract] [Full Text] [Related]
[Next] [New Search]
