Browsing by Author "Tharian, Benjamin"

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    The Evolution of Device-Assisted Enteroscopy: From Sonde Enteroscopy to Motorized Spiral Enteroscopy
    (Frontiers Media, 2021) Nehme, Fredy; Goyal, Hemant; Perisetti, Abhilash; Tharian, Benjamin; Sharma, Neil; Tham, Tony C.; Chhabra, Rajiv; Medicine, School of Medicine
    The introduction of capsule endoscopy in 2001 opened the last "black box" of the gastrointestinal tract enabling complete visualization of the small bowel. Since then, numerous new developments in the field of deep enteroscopy have emerged expanding the diagnostic and therapeutic armamentarium against small bowel diseases. The ability to achieve total enteroscopy and visualize the entire small bowel remains the holy grail in enteroscopy. Our journey in the small bowel started historically with sonde type enteroscopy and ropeway enteroscopy. Currently, double-balloon enteroscopy, single-balloon enteroscopy, and spiral enteroscopy are available in clinical practice. Recently, a novel motorized enteroscope has been described with the potential to shorten procedure time and allow for total enteroscopy in one session. In this review, we will present an overview of the currently available techniques, indications, diagnostic yield, and complications of device-assisted enteroscopy.
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    Scope of Artificial Intelligence in Screening and Diagnosis of Colorectal Cancer
    (MDPI, 2020-10-15) Goyal, Hemant; Mann, Rupinder; Gandhi, Zainab; Perisetti, Abhilash; Ali, Aman; Aman Ali, Khizar; Sharma, Neil; Saligram, Shreyas; Tharian, Benjamin; Inamdar, Sumant; Medicine, School of Medicine
    Globally, colorectal cancer is the third most diagnosed malignancy. It causes significant mortality and morbidity, which can be reduced by early diagnosis with an effective screening test. Integrating artificial intelligence (AI) and computer-aided detection (CAD) with screening methods has shown promising colorectal cancer screening results. AI could provide a "second look" for endoscopists to decrease the rate of missed polyps during a colonoscopy. It can also improve detection and characterization of polyps by integration with colonoscopy and various advanced endoscopic modalities such as magnifying narrow-band imaging, endocytoscopy, confocal endomicroscopy, laser-induced fluorescence spectroscopy, and magnifying chromoendoscopy. This descriptive review discusses various AI and CAD applications in colorectal cancer screening, polyp detection, and characterization.