This study uses hyperspectral imaging (HSI) and a deep learning diagnosis model that can identify the stage of esophageal cancer and mark the locations. This model simulates the spectrum data from the image using an algorithm developed in this study which is combined with deep learning for the classification and diagnosis of esophageal cancer using a single-shot multibox detector (SSD)-based identification system. Some 155 white-light endoscopic images and 153 narrow-band endoscopic images of esophageal cancer were used to evaluate the prediction model. The algorithm took 19 s to predict the results of 308 test images and the accuracy of the test results of the WLI and NBI esophageal cancer was 88 and 91%, respectively, when using the spectral data. Compared with RGB images, the accuracy of the WLI was 83% and the NBI was 86%. In this study, the accuracy of the WLI and NBI was increased by 5%, confirming that the prediction accuracy of the HSI detection method is significantly improved.

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Esophageal neuroendocrine neoplasms (NEN) are extremely rare and little is known about their risk factors. To identify the potential risk factors, we evaluated whether the history of substance use, including alcohol, tobacco and areca nut consumption was associated with esophageal NEN. Forty-one esophageal NEN patients diagnosed between 2002 and 2019 from 17 hospital in Taiwan were enrolled as the cases.Controls were participants who received complete esophagogastroduodenoscopy in an endoscopic cohort and 123 eligible controls were matched to 41 cases (3:1) on age and gender. Alcohol drinking and cigarette smoking significantly increased the risk of esophageal NEN, with about a fourfold risk increase in alcohol drinkers as well as cigarette smokers. Moreover, use of cigarette smoking and alcohol consumption in combination demonstrated the highest risk of esophageal NEN with the risk increasing up to 20 times compared with non-users. Alcohol consumption and cigarette smoking significantly increase risk of esophageal NEN and both alcohol and cigarette users had the highest risk.