Gastrointestinal polyps are considered to be the precursors of cancer development in most of the cases. Therefore, early detection and removal of polyps can reduce the possibility of cancer. Video endoscopy is the most used diagnostic modality for gastrointestinal polyps. But, because it is an operator dependent procedure, several human factors can lead to misdetection of polyps. Computer aided polyp detection can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention to. In this paper, an automatic system has been proposed as a support to gastrointestinal polyp detection. This system captures the video streams from endoscopic video and, in the output, it shows the identified polyps. Color wavelet (CW) features and convolutional neural network (CNN) features of video frames are extracted and combined together which are used to train a linear support vector machine (SVM). Evaluations on standard public databases show that the proposed system outperforms the state-of-the-art methods, gaining accuracy of 98.65%, sensitivity of 98.79%, and specificity of 98.52%.

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Introduction Diabetes distress (DD) is common and has considerable impacts on diabetes management. Unfortunately, DD is less discussed and frequently underestimated. This study evaluated the prevalence and predictors of DD in adults with type 2 diabetes mellitus (T2DM). Methods A cross-sectional study was conducted at several specialized endocrinology outpatient clinics in Bangladesh from July 2019 to June 2020; 259 adults with T2DM participated. Participants’ DD and depression were measured using the 17-item Diabetes Distress Scale (DDS-17) and 9-item Patient Health Questionnaire (PHQ-9), respectively. DDS-17 scores ≥2 and PHQ-9 scores ≥10 were the cutoffs for DD and significant depression, respectively. Results The mean (±SD) age of the participants was 50.36 (±12.7) years, with the majority (54.8%) being male; their median (IQR) duration of diabetes was 6 (3–11) years. Among the study participants, 52.5% had DD (29.7% moderate and 22.8% high DD). The prevalence of emotional burden, physician-related distress, regimen-related distress, and interpersonal distress was 68.7, 28.6, 66, and 37.7%, respectively. Depression was present in 40.5%; 28.6% of the participants had DD and depression. The total DDS-17 score was positively correlated with the PHQ-9 score (r = 0.325, p < 0.001). Rural residence (OR 1.94), presence of any diabetic complication (OR 3.125), insulin use (OR 2.687), and presence of major depression (OR 4.753) were positive predictors of DD. In contrast, age ≥ 40 years at diabetes diagnosis (OR 0.047) and diabetes duration of > 10 years (OR 0.240) were negative predictors of DD (p < 0.05 in all instances). Conclusions The prevalence of DD in our setting is notably high; DD and depression frequently overlap. Screening for diabetes distress may be considered, especially in high-risk patients.

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