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Volumn 9, Issue 6, 2016, Pages 618-620

Learning about Machine Learning: The Promise and Pitfalls of Big Data and the Electronic Health Record

Author keywords

Editorials; heart failure; linear models; machine learning; medicine; risk factors

Indexed keywords

CLINICAL DECISION MAKING; CLINICAL DECISION SUPPORT SYSTEM; COHORT ANALYSIS; DATA MINING; EDITORIAL; ELECTRONIC HEALTH RECORD; HEALTH CARE COST; HEALTH SERVICE; HEART FAILURE; HOSPITALIZATION; HUMAN; INCIDENCE; KNOWLEDGE; LOGISTIC REGRESSION ANALYSIS; MACHINE LEARNING; OUTCOMES RESEARCH; PATIENT CODING; PHYSICAL EXAMINATION; PHYSICIAN; PHYSICIAN ATTITUDE; PRACTICE GUIDELINE; PRIORITY JOURNAL; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; RESPONSE VARIABLE;

EID: 84995917328     PISSN: 19417713     EISSN: 19417705     Source Type: Journal    
DOI: 10.1161/CIRCOUTCOMES.116.003308     Document Type: Editorial
Times cited : (35)

References (5)
  • 2
    • 84947466043 scopus 로고    scopus 로고
    • Machine learning in medicine
    • Deo RC, Machine learning in medicine. Circulation 2015 132 1920 1930. doi: 10.1161/CIRCULATIONAHA.115.001593
    • (2015) Circulation , vol.132 , pp. 1920-1930
    • Deo, R.C.1
  • 3
    • 84995946079 scopus 로고    scopus 로고
    • Early detection of heart failure using electronic health records: Practical implications for time before diagnosis, data diversity, data quantity, and data density
    • Ng K, Steinhubl SR, deFilippi C, Dey S, Stewart WF, Early detection of heart failure using electronic health records: practical implications for time before diagnosis, data diversity, data quantity, and data density. Circ Cardiovasc Qual Outcomes 2016 9 649 658. doi: 10.1161/CIRCOUTCOMES.116.002797
    • (2016) Circ Cardiovasc Qual Outcomes , vol.9 , pp. 649-658
    • Ng, K.1    Steinhubl, S.R.2    DeFilippi, C.3    Dey, S.4    Stewart, W.F.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.