Prediction of HCV vertical transmission: what factors should be optimized using data mining computational analysis

Liver International

Volumn 37, Issue 4, 2017, Pages 529-533

  Elrazek, Abd ^a   Amer, Mohamed ^b   El Hawary, Bahaa ^a   Salah, Altaher ^c   Bhagavathula, Akshaya S ^d   Alboraie, M ^e   Saab, Samy ^f  

^a ASWAN UNIVERSITY   (Egypt)

^b MENOUFIA UNIVERSITY   (Egypt)

^c MINISTRY OF HEALTH   (Egypt)

^d UNIVERSITY OF GONDAR   (Ethiopia)

^e AL AZHAR UNIVERSITY   (Egypt)

^f UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

delivery; hepatitis C virus; pregnancy; vertical transmission

Indexed keywords

CHILD; CONTROLLED CLINICAL TRIAL; DATA MINING; EGYPT; FEMALE; HEPATITIS C VIRUS; HUMAN; MAJOR CLINICAL STUDY; NEWBORN; PREDICTION; PREGNANCY; PREGNANT WOMAN; PREVALENCE; QUANTITATIVE STUDY; RANDOMIZED CONTROLLED TRIAL; SCREENING; VERTICAL TRANSMISSION; VIRUS LOAD; VIRUS TRANSMISSION; ADULT; HEPACIVIRUS; HEPATITIS C; MASS SCREENING; PREGNANCY COMPLICATION; PROSPECTIVE STUDY; RISK FACTOR; TRANSMISSION; VIROLOGY; YOUNG ADULT;

VIRUS RNA;

ADULT; DATA MINING; EGYPT; FEMALE; HEPACIVIRUS; HEPATITIS C; HUMANS; INFANT, NEWBORN; INFECTIOUS DISEASE TRANSMISSION, VERTICAL; MASS SCREENING; PREGNANCY; PREGNANCY COMPLICATIONS, INFECTIOUS; PROSPECTIVE STUDIES; RISK FACTORS; RNA, VIRAL; VIRAL LOAD; YOUNG ADULT;

EID: 84977103161     PISSN: 14783223     EISSN: 14783231     Source Type: Journal    
DOI: 10.1111/liv.13146     Document Type: Article

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