168 related articles for article (PubMed ID: 33799968)
1. Predicting Survival in Veterans with Follicular Lymphoma Using Structured Electronic Health Record Information and Machine Learning.
Li C; Patil V; Rasmussen KM; Yong C; Chien HC; Morreall D; Humpherys J; Sauer BC; Burningham Z; Halwani AS
Int J Environ Res Public Health; 2021 Mar; 18(5):. PubMed ID: 33799968
[TBL] [Abstract][Full Text] [Related]
2. Detection of probable dementia cases in undiagnosed patients using structured and unstructured electronic health records.
Shao Y; Zeng QT; Chen KK; Shutes-David A; Thielke SM; Tsuang DW
BMC Med Inform Decis Mak; 2019 Jul; 19(1):128. PubMed ID: 31288818
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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]
5. Rule-based and machine learning algorithms identify patients with systemic sclerosis accurately in the electronic health record.
Jamian L; Wheless L; Crofford LJ; Barnado A
Arthritis Res Ther; 2019 Dec; 21(1):305. PubMed ID: 31888720
[TBL] [Abstract][Full Text] [Related]
6. Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer.
Yuan Q; Cai T; Hong C; Du M; Johnson BE; Lanuti M; Cai T; Christiani DC
JAMA Netw Open; 2021 Jul; 4(7):e2114723. PubMed ID: 34232304
[TBL] [Abstract][Full Text] [Related]
7. Electronic phenotyping of health outcomes of interest using a linked claims-electronic health record database: Findings from a machine learning pilot project.
Gibson TB; Nguyen MD; Burrell T; Yoon F; Wong J; Dharmarajan S; Ouellet-Hellstrom R; Hua W; Ma Y; Baro E; Bloemers S; Pack C; Kennedy A; Toh S; Ball R
J Am Med Inform Assoc; 2021 Jul; 28(7):1507-1517. PubMed ID: 33712852
[TBL] [Abstract][Full Text] [Related]
8. GRU-D-Weibull: A novel real-time individualized endpoint prediction.
Ruan X; Wang L; Thongprayoon C; Cheungpasitporn W; Liu H
Artif Intell Med; 2023 Dec; 146():102696. PubMed ID: 38042597
[TBL] [Abstract][Full Text] [Related]
9. Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease.
Steele AJ; Denaxas SC; Shah AD; Hemingway H; Luscombe NM
PLoS One; 2018; 13(8):e0202344. PubMed ID: 30169498
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Accurate Prediction of Coronary Heart Disease for Patients With Hypertension From Electronic Health Records With Big Data and Machine-Learning Methods: Model Development and Performance Evaluation.
Du Z; Yang Y; Zheng J; Li Q; Lin D; Li Y; Fan J; Cheng W; Chen XH; Cai Y
JMIR Med Inform; 2020 Jul; 8(7):e17257. PubMed ID: 32628616
[TBL] [Abstract][Full Text] [Related]
12. Dynamic ElecTronic hEalth reCord deTection (DETECT) of individuals at risk of a first episode of psychosis: a case-control development and validation study.
Raket LL; Jaskolowski J; Kinon BJ; Brasen JC; Jönsson L; Wehnert A; Fusar-Poli P
Lancet Digit Health; 2020 May; 2(5):e229-e239. PubMed ID: 33328055
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Machine Learning-Based Prognostic Model for Patients After Lung Transplantation.
Tian D; Yan HJ; Huang H; Zuo YJ; Liu MZ; Zhao J; Wu B; Shi LZ; Chen JY
JAMA Netw Open; 2023 May; 6(5):e2312022. PubMed ID: 37145595
[TBL] [Abstract][Full Text] [Related]
15. Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.
Lin C; Hsu CJ; Lou YS; Yeh SJ; Lee CC; Su SL; Chen HC
J Med Internet Res; 2017 Nov; 19(11):e380. PubMed ID: 29109070
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Identifying and Predicting Intentional Self-Harm in Electronic Health Record Clinical Notes: Deep Learning Approach.
Obeid JS; Dahne J; Christensen S; Howard S; Crawford T; Frey LJ; Stecker T; Bunnell BE
JMIR Med Inform; 2020 Jul; 8(7):e17784. PubMed ID: 32729840
[TBL] [Abstract][Full Text] [Related]
18. Early Prediction of Neoplasms Using Machine Learning: A Study of Electronic Health Records from the Ministry of National Guard Health Affairs in Saudi Arabia.
Abdullah Alfayez A; Grace Lai A; Kunz H
Stud Health Technol Inform; 2022 Jan; 289():37-40. PubMed ID: 35062086
[TBL] [Abstract][Full Text] [Related]
19. Accuracy of electronic health record data for the diagnosis of chronic obstructive pulmonary disease in persons living with HIV and uninfected persons.
Crothers K; Rodriguez CV; Nance RM; Akgun K; Shahrir S; Kim J; W Soo Hoo G; Sharafkhaneh A; Crane HM; Justice AC
Pharmacoepidemiol Drug Saf; 2019 Feb; 28(2):140-147. PubMed ID: 29923258
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
