1422 related articles for article (PubMed ID: 28376093)
1. Can machine-learning improve cardiovascular risk prediction using routine clinical data?
Weng SF; Reps J; Kai J; Garibaldi JM; Qureshi N
PLoS One; 2017; 12(4):e0174944. PubMed ID: 28376093
[TBL] [Abstract][Full Text] [Related]
2. Predicting post-stroke pneumonia using deep neural network approaches.
Ge Y; Wang Q; Wang L; Wu H; Peng C; Wang J; Xu Y; Xiong G; Zhang Y; Yi Y
Int J Med Inform; 2019 Dec; 132():103986. PubMed ID: 31629312
[TBL] [Abstract][Full Text] [Related]
3. Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants.
Alaa AM; Bolton T; Di Angelantonio E; Rudd JHF; van der Schaar M
PLoS One; 2019; 14(5):e0213653. PubMed ID: 31091238
[TBL] [Abstract][Full Text] [Related]
4. Prediction of premature all-cause mortality: A prospective general population cohort study comparing machine-learning and standard epidemiological approaches.
Weng SF; Vaz L; Qureshi N; Kai J
PLoS One; 2019; 14(3):e0214365. PubMed ID: 30917171
[TBL] [Abstract][Full Text] [Related]
5. Dynamic prediction of psychological treatment outcomes: development and validation of a prediction model using routinely collected symptom data.
Bone C; Simmonds-Buckley M; Thwaites R; Sandford D; Merzhvynska M; Rubel J; Deisenhofer AK; Lutz W; Delgadillo J
Lancet Digit Health; 2021 Apr; 3(4):e231-e240. PubMed ID: 33766287
[TBL] [Abstract][Full Text] [Related]
6. Machine-learning prediction of adolescent alcohol use: a cross-study, cross-cultural validation.
Afzali MH; Sunderland M; Stewart S; Masse B; Seguin J; Newton N; Teesson M; Conrod P
Addiction; 2019 Apr; 114(4):662-671. PubMed ID: 30461117
[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. 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]
9. A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.
Dinh A; Miertschin S; Young A; Mohanty SD
BMC Med Inform Decis Mak; 2019 Nov; 19(1):211. PubMed ID: 31694707
[TBL] [Abstract][Full Text] [Related]
10. Machine learning applications for the prediction of surgical site infection in neurological operations.
Tunthanathip T; Sae-Heng S; Oearsakul T; Sakarunchai I; Kaewborisutsakul A; Taweesomboonyat C
Neurosurg Focus; 2019 Aug; 47(2):E7. PubMed ID: 31370028
[TBL] [Abstract][Full Text] [Related]
11. Chronic stress in practice assistants: An analytic approach comparing four machine learning classifiers with a standard logistic regression model.
Bozorgmehr A; Thielmann A; Weltermann B
PLoS One; 2021; 16(5):e0250842. PubMed ID: 33945572
[TBL] [Abstract][Full Text] [Related]
12. Machine learning to predict cardiovascular risk.
Quesada JA; Lopez-Pineda A; Gil-Guillén VF; Durazo-Arvizu R; Orozco-Beltrán D; López-Domenech A; Carratalá-Munuera C
Int J Clin Pract; 2019 Oct; 73(10):e13389. PubMed ID: 31264310
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Predicting hospitalization following psychiatric crisis care using machine learning.
Blankers M; van der Post LFM; Dekker JJM
BMC Med Inform Decis Mak; 2020 Dec; 20(1):332. PubMed ID: 33302948
[TBL] [Abstract][Full Text] [Related]
15. Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer.
Parikh RB; Manz C; Chivers C; Regli SH; Braun J; Draugelis ME; Schuchter LM; Shulman LN; Navathe AS; Patel MS; O'Connor NR
JAMA Netw Open; 2019 Oct; 2(10):e1915997. PubMed ID: 31651973
[TBL] [Abstract][Full Text] [Related]
16. Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions.
Lo-Ciganic WH; Huang JL; Zhang HH; Weiss JC; Wu Y; Kwoh CK; Donohue JM; Cochran G; Gordon AJ; Malone DC; Kuza CC; Gellad WF
JAMA Netw Open; 2019 Mar; 2(3):e190968. PubMed ID: 30901048
[TBL] [Abstract][Full Text] [Related]
17. Construction of a predictive model for radiation proctitis after radiotherapy for female pelvic tumors based on machine learning.
Xie H; Gong M; Zhang J; Li Q
Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2022 Aug; 47(8):1065-1074. PubMed ID: 36097774
[TBL] [Abstract][Full Text] [Related]
18. Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards.
Churpek MM; Yuen TC; Winslow C; Meltzer DO; Kattan MW; Edelson DP
Crit Care Med; 2016 Feb; 44(2):368-74. PubMed ID: 26771782
[TBL] [Abstract][Full Text] [Related]
19. [Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].
Tang CQ; Li JQ; Xu DY; Liu XB; Hou WJ; Lyu KY; Xiao SC; Xia ZF
Zhonghua Shao Shang Za Zhi; 2018 Jun; 34(6):343-348. PubMed ID: 29961290
[No Abstract] [Full Text] [Related]
20. Identification of newborns at risk for autism using electronic medical records and machine learning.
Rahman R; Kodesh A; Levine SZ; Sandin S; Reichenberg A; Schlessinger A
Eur Psychiatry; 2020 Feb; 63(1):e22. PubMed ID: 32100657
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
