zohreh ansari

Deep learning has gained much attention in computer‐assisted minimally invasive surgery in recent years. The application of deep‐learning algorithms in colonoscopy can be divided into four main categories: surgical image analysis, surgical operations analysis, evaluation of surgical skills, and surgical automation. Analysis of surgical images by deep learning can be one of the main solutions for early detection of gastrointestinal lesions and for taking appropriate actions to treat cancer.

This study investigates a simple and accurate deep‐learning model for polyp detection. We address the challenge of limited labeled data through transfer learning and employ multi‐task learning to achieve both polyp classification and bounding box detection tasks. Considering the appropriate weight for each task in the total cost function is crucial in achieving the best results. Due to the lack of datasets with nonpolyp images, data collection was carried out. The proposed deep neural network structure was implemented on KVASIR‐SEG and CVC‐CLINIC datasets as polyp images in addition to the nonpolyp images extracted from the LDPolyp videos dataset.

The proposed model demonstrated high accuracy, achieving 100% in polyp/non-polyp classification and 86% in bounding box detection. It also showed fast processing times (0.01 seconds), making it suitable for real-time clinical applications.

The developed deep-learning model offers an efficient, accurate, and cost-effective solution for real-time polyp detection in colonoscopy. Its performance on benchmark datasets confirms its potential for clinical deployment, aiding in early cancer diagnosis and treatment.

 The aim of this study was to determine the effectiveness of emotion-oriented couple therapy and compare it with structural couple therapy on marital justice and relationship maintenance strategies in conflicting couples. 

 The present study was a quasi-experimental with pre-test and post-test with a two-month control and follow-up group; The statistical population of the present study was 205 couples referring to counseling centers in Shiraz in the last six months of 1399. After screening with the Sanai Marital Conflict Questionnaire (2008), 60 couples who received more than 150 points from the cut-off point were selected by available means. They answered the Marital Justice Questionnaire and Relationship Strategies (Stafford, Dinton and Haas, 2000) and in the experimental group of emotion-focused couple therapy (10 couples), the experimental group of structural couple therapy (10 couples) and the control group (10 couples) were randomly replaced. Both experimental groups underwent Johnson (2004) emotion-focused couple therapy and Minochin (1974) structural couple therapy intervention for eight 90-minute sessions, and the control group did not receive any intervention. Data were analyzed using repeated measures mixed variance analysis. 

 The results showed that emotion-oriented couple therapy (F = 8.97 and P = 0.005) and structural couple therapy (F = 10.04 and P = 0.003) on increasing marital justice and emotion-oriented couple therapy (0.60). F = 59 and P = 0.001) and structural couple therapy (F = 19.29 and P = 0.001) are effective in maintaining relationship strategies in conflicting couples and this effect was stable in the follow-up phase; The results of post hoc test also showed that the difference between the two groups of emotion-oriented couple therapy and structural couple therapy in marital justice variables and strategies for maintaining the relationship is not significant. 

 The results of the research suggest evidence that the intervention of emotion-oriented couple therapy and structural couple therapy is a suitable method for increasing marital justice and relationship maintenance strategies in spouses suffering from marital conflict.

Among the common mental disorders in societies, depression is one of the most common mental disorders that affects all groups and classes of society. Students are among the groups with the highest rates of depression. Therefore, the need for a short and effective tool for screening and early detection of depression is felt. The aim of this research is to determine validity, reliability and the best cut‑off point of the patient health questionnaires‑9 (PHQ‑9) and patient health questionnaires‑2 (PHQ‑2) in university students.

This cross‑sectional study was conducted on 246 students of Kermanshah University of medical science in Kermanshah province of Iran. They completed the PHQ‑2, PHQ‑9, and the Beck Depression Inventory‑II (BDI‑II). A structured interview was used to diagnose depression. To analyze the data, Cronbach’s alpha for internal consistency, the intra‑class correlation (ICC) for test–retest reliability, confirmatory factor analysis for construct validity, Pearson Correlation for Convergent validity, and receiver‑operating characteristic (ROC) curve for Criterion validity was used.

The mean age of the participants was 20.43 ± 2.29. Cronbach’s alpha coefficient for PHQ‑9 and PHQ‑2 was 0.82 and 0.80, respectively. The test–retest reliability based on intra‑class correlation (ICC) for PHQ‑9 and PHQ‑2 after two weeks was 0.81 and 0.73, respectively (P < 0.001). The correlation coefficient between the PHQ‑9 and PHQ‑2 with the BDI‑II was 0.74 and 0.64, respectively (P < 0.001). Confirmatory factor analysis showed that two-factor model and one factor model had good model fit. The best cut‑off point score for the PHQ‑9 was 10 with a sensitivity of 0.90 and specificity of 0.93, and the best cut‑off point score for the PHQ‑2 was 3 with the sensitivity of 0.71 and specificity of 0.92.

The PHQ‑9 and PHQ‑2 are suitable tools to screen depression in the university students in Iran.