Natural language processing (NLP) is a computer technology that uses language cues and context to interpret findings and mine large databases to identify desired clinical

The current screening model for Barrett’s esophagus (BE) has limitations because patients need to be identified by their primary care physician and then referred to

Endoscopic surveillance of Barrett’s esophagus (BE) is recommended to reduce mortality and morbidity related to esophageal adenocarcinoma. A thorough endoscopic inspection of a BE segment

Barrett’s esophagus (BE)-related neoplasia is frequently missed during upper endoscopy, and characterization of mucosal changes may help in its detection. The primary aim of this

Barrett’s esophagus (BE) is a precancerous condition that can lead to the development of dysplasia and esophageal adenocarcinoma (neoplasia). Since neoplasia can present as subtle

Genome-wide association studies (GWAS) involve scanning the DNA of a large cohort to identify any genetic variants associated with the disease in question. Previous GWAS

Natural language processing (NLP) is a branch of artificial intelligence (AI) systems that involves teaching computers the ability to understand written text like how humans

Endoscopic therapy for patients with neoplastic Barrett’s esophagus (BE) involves resection followed by mucosal ablation. Radiofrequency ablation (RFA) of the flat BE mucosa leads to

Current strategies for the endoscopic treatment of Barrett’s esophagus (BE) focus on resection of nodular lesions within BE and then the ablation of the flat

The degree of dysplasia in patients with Barrett’s esophagus (BE) is key to determining the application of BE endoscopic therapy and assigning surveillance intervals. Multiple

A small subset of patients who undergo Barrett’s endoscopic therapy (BET) using radiofrequency ablation (RFA) will have evidence of poor mucosal healing (mucosal edema, ulcers,

Barrett’s esophagus (BE) is a known precancerous lesion for esophageal dysplasia and adenocarcinoma (EAC); however, it is unclear who will progress to high-grade dysplasia (HGD)

Endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) have emerged as important treatment techniques for patients with visible lesions in Barrett’s esophagus (BE). Whereas

Endoscopic therapy for Barrett’s esophagus (BE) usually involves resection of visible lesions by endoscopic mucosal resection followed by mucosal ablation using radio frequency ablation. Hybrid

Radiofrequency ablation (RFA) is widely utilized in the treatment of neoplastic Barrett’s esophagus (BE) after endoscopic resection of all visible lesions. Cryotherapy is another form

The accurate diagnosis and management of patients with Barrett’s esophagus (BE) are important for the early recognition and minimally invasive treatment of BE neoplasia. Despite

The incidence of esophageal adenocarcinoma (EAC) continues to increase and is still associated with a poor prognosis with a 5-year survival rate of 20%. The

During endoscopy, the extent of Barrett’s esophagus (BE) is quantified by endoscopists using the widely accepted Prague C&M (circumferential and maximal lengths) criteria. Prague C&M

Patients with high-grade dysplasia and/or early cancer in Barrett’s esophagus (BE) are treated with endoscopic therapy (BET), with the goal of complete eradication of all

Buried Barrett’s esophagus (BE) mucosa, or subsquamous intestinal metaplasia, is defined as intestinal metaplasia that is present under a lining of endoscopically intact squamous epithelium.

Achalasia can cause food retention, leading to bacterial overgrowth, irritation, and chronic inflammation, a proposed pathophysiological process that may lead to squamous cell carcinoma (SCC).

Upper endoscopy (EGD) with biopsy remains the gold standard for the diagnosis of Barrett’s esophagus (BE). Several nonendoscopic techniques (sponge, capsule) have utilized biomarkers, such

Douglas K. Rex, MD, FASGE, reviewing Parsa N, et al. Gastrointest Endosc 2020 Feb 4. In a single U.S. center with a large experience performing