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Cecum

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Predicting postmortem interval based on microbial community sequences and machine learning algorithms.

Environmental microbiology
Microbes play an essential role in the decomposition process but were poorly understood in their succession and behaviour. Previous researches have shown that microbes show predictable behaviour that starts at death and changes during the decompositi...

Application of optical character recognition with natural language processing for large-scale quality metric data extraction in colonoscopy reports.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Colonoscopy is commonly performed for colorectal cancer screening in the United States. Reports are often generated in a non-standardized format and are not always integrated into electronic health records. Thus, this information...

Development and validation of a deep learning-based algorithm for colonoscopy quality assessment.

Surgical endoscopy
BACKGROUND: Quality indicators should be assessed and monitored to improve colonoscopy quality in clinical practice. Endoscopists must enter relevant information in the endoscopy reporting system to facilitate data collection, which may be inaccurate...

A case of robot-assisted resection for cecum cancer with anomalous venous confluence.

Asian journal of endoscopic surgery
There are many reports on the positional relationship between the ileocolic artery and superior mesenteric vein (SMV). However, there have been no reports of anomalous venous confluence in the ileocecal vessel area. A 69-year-old man was diagnosed wi...

Effect of a novel artificial intelligence-based cecum recognition system on adenoma detection metrics in a screening colonoscopy setting.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Cecal intubation in colonoscopy relies on self-reporting. We developed an artificial intelligence-based cecum recognition system (AI-CRS) for post-hoc verification of cecal intubation and explored its impact on adenoma metrics.