ARTIFICIAL INTELLIGENCE AUTOMATES EVALUATION OF BASELINE IMPEDANCE FROM PH-IMPEDANCE STUDIES AND PREDICTS SYMPTOM OUTCOME IN GASTRO-ESOPHAGEAL REFLUX DISEASE (GERD)

被引：0
|
作者：
Rogers, Benjamin D.
Samanta, Sabyasachi
Ghobadi, Kevan
Patel, Amit
Savarino, Edoardo V.
Roman, Sabine
Sifrim, Daniel
Gyawali, C. Prakash
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来源：
GASTROENTEROLOGY | 2020年 / 158卷 / 06期
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D O I：
暂无
中图分类号：
R57 [消化系及腹部疾病];
学科分类号：
摘要：
149
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页码：S32 / S32
页数：1
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  • [1] Artificial intelligence complements evaluation of baseline impedance from pH-impedance studies and predicts outcome in gastro-esophageal reflux disease (GERD)
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  • [2] Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease
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    Ghobadi, Kevan
    Patel, Amit
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    Sifrim, Daniel
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    JOURNAL OF GASTROENTEROLOGY, 2021, 56 (01) : 34 - 41
  • [3] Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease
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    Journal of Gastroenterology, 2021, 56 : 34 - 41
  • [4] Distal mean nocturnal baseline impedance on pH-impedance monitoring predicts reflux burden and symptomatic outcome in gastro-oesophageal reflux disease
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