Improvement for Diagnosis of Gastric Cancer from Endoscopic Images using Machine Learning

Detection of cancer disease in any part of a human body is of utmost importance as it can be cured completely.  In this research work, a prognosis of early gastric cancer detection by applying modern machine learning algorithms augmented with fast and efficient classification of white light images. In earlier studies for early gastric cancer detection schemes, nominal endoscopic images demand more computational effort, which slows down process and takes more time. Moreover, in the contemporary methodologies, only basic parameters were used to detect the symptoms of gastric cancer such as accuracy. Whilst in the proposed methodology, protein structure of the cancerous part is also examined with the help of Alpha fold software. A dataset consist of white-light-images is developed from the endoscopic images of the suspected patients. By utilitarian of this dataset in the proposed scheme, results are drawn which shows greater accuracy at a lower cost as compared to contemporary techniques

Investor sentiment and stock price crash risk: The mediating role of analyst herding

This study analyzes the impact of investor sentiment on firm's stock price crash risk by using Chinese A-Share firms data this study assesses the potency and existence of a relationship between crash risk and investor sentiment in the Chinese stock market and introduces analyst herding as a mediating variable for explaining the relationship between crash risk and investor sentiment. By utilizing a large data set of A-share listed firms on Chinese stock exchanges, comprising of 19,371 firm-year observations for the period of 2004–2019, an investor sentiment index is constructed. Results point towards a positive significant relation between stock price crash risk and investor sentiment. Furthermore, stock price crash is positively correlated with analyst herding i.e. it significantly mediates between stock price crash risk and investor sentiment. By measuring the relationship between crash risk, investor sentiment, and analyst herding this study provides systematic support on the mediating role of analyst herding in deepening the market sentiment which results in crash risk. These findings are robust by utilizing alternate proxies and controlling for firm specific variables, economy-wide shocks, and time trends year fixed effects

Self-reported health and smoking status, and body mass index: a case-control comparison based on GEN SCRIP (GENetics of SChizophRenia In Pakistan) data

Introduction Individuals with schizophrenia are at a high risk of physical health comorbidities and premature mortality. Cardiovascular and metabolic causes are an important contributor. There are gaps in monitoring, documenting and managing these physical health comorbidities. Because of their condition, patients themselves may not be aware of these comorbidities and may not be able to follow a lifestyle that prevents and manages the complications. In many low-income and middle-income countries including Pakistan, the bulk of the burden of care for those struggling with schizophrenia falls on the families.Objectives To determine the rate of self-reported physical health disorders and risk factors, like body mass index (BMI) and smoking, associated with cardiovascular and metabolic disorders in cases of schizophrenia compared with a group of mentally healthy controls.Design A case-controlled, cross-sectional multicentre study of patients with schizophrenia in Pakistan.Settings Multiple data collection sites across the country for patients, that is, public and private psychiatric OPDs (out patient departments), specialised psychiatric care facilities, and psychiatric wards of teaching and district level hospitals. Healthy controls were enrolled from the community.Participants We report a total of 6838 participants’ data with (N 3411 (49.9%)) cases of schizophrenia compared with a group of healthy controls (N 3427 (50.1%)).Results BMI (OR 0.98 (CI 0.97 to 0.99), p=0.0025), and the rate of smoking is higher in patients with schizophrenia than in controls. Problems with vision (OR 0.13 (0.08 to 0.2), joint pain (OR 0.18 (0.07 to 0.44)) and high cholesterol (OR 0.13 (0.05 to 0.35)) have higher reported prevalence in controls. The cases describe more physical health disorders in the category ‘other’ (OR 4.65 (3.01 to 7.18)). This captures residual disorders not listed in the questionnaire.Conclusions Participants with schizophrenia in comparison with controls report more disorders. The access in the ‘other’ category may be a reflection of undiagnosed disorders