review Open AccessTop 1% cited
Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis
Gastrointestinal Endoscopy · 2020 · Vol. 93(1) · pp. 77–85.e6
Cesare Hassan(Ospedale Regina Margherita)Marco Spadaccini✉(Istituti di Ricovero e Cura a Carattere Scientifico)Andrea Iannone(University of Bari Aldo Moro)Roberta Maselli(Humanitas University)Manol Jovani(Johns Hopkins Hospital)Viveksandeep Thoguluva Chandrasekar(Kansas City VA Medical Center)Giulio Antonelli(Ospedale Regina Margherita)Honggang Yu(Renmin Hospital of Wuhan University)Miguel Areia(Instituto Português de Oncologia Francisco Gentil)Mário Dinis‐Ribeiro(Decision Sciences (United States))Pradeep Bhandari(Queen Alexandra Hospital)Prateek Sharma(Kansas City VA Medical Center)Douglas K. Rex(Indiana University – Purdue University Indianapolis)Thomas Rösch(Universität Hamburg)Michael B. Wallace(Mayo Clinic in Florida)Alessandro Repici(Istituti di Ricovero e Cura a Carattere Scientifico)
Colorectal Cancer Screening and DetectionGastric Cancer Management and OutcomesRadiomics and Machine Learning in Medical ImagingMedicineColonoscopyMeta-analysisAdenomaGastroenterologyInternal medicineGeneral surgeryColorectal cancerCancer
MeSH terms
AdenomaArtificial IntelligenceColonic PolypsColonoscopyHumansColorectal Neoplasms
Citations
475
FWCI
24.69
field-weighted impact
References
26
Percentile
100%
vs. same field & year
Citations per year
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References
Colonoscopic miss rates of adenomas determined by back-to-back colonoscopies
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BMC Health Services Research · 2004 · 1,210 citations
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Journal of Clinical Epidemiology · 2009 · 19,782 citations
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