GENDER DIFFERENCE IN UNDERSTANDING AGEING AND RETIREMENT

@#The age-old wisdom is that “women live longer than men”. Gender difference in life expectancy is becoming a worldwide phenomenon both in developed and developing countries. The process of ageing may be viewed from the perspectives of physical, psychological, and social-economic wellbeing. We investigated gender difference in understanding ageing in relation to life expectancy, fears relating to diseases and deteriorating economic status, and perceived old age comfort and their preparedness. Data were obtained from an online survey and in-person interview of 518 respondents aged 40 years and older residing in Malaysia, which was based on a convenience sample collected from May 2015 to January 2016. Data were analysed using chi-squared tests and multinomial logistic regression. There were varying views between men and women when it came to understanding ageing in relation to life expectancy, fears of ageing, deteriorating economic status and their perception of old age comfort. Women were more optimistic about living longer compared to men but feared more the consequences of old age diseases. In spite of displaying less concern about financial preparedness, women were, however, willing to cut down expenses, while men would prefer longer working hours to ensure a comfortable retirement

Automatic Glaucoma Detection Method Applying a Statistical Approach to Fundus Images / 대한의료정보학회지

OBJECTIVES: Glaucoma is an incurable eye disease and the second leading cause of blindness in the world. Until 2020, the number of patients of this disease is estimated to increase. This paper proposes a glaucoma detection method using statistical features and the k-nearest neighbor algorithm as the classifier. METHODS: We propose three statistical features, namely, the mean, smoothness and 3rd moment, which are extracted from images of the optic nerve head. These three features are obtained through feature extraction followed by feature selection using the correlation feature selection method. To classify those features, we apply the k-nearest neighbor algorithm as a classifier to perform glaucoma detection on fundus images. RESULTS: To evaluate the performance of the proposed method, 84 fundus images were used as experimental data consisting of 41 glaucoma image and 43 normal images. The performance of our proposed method was measured in terms of accuracy, and the overall result achieved in this work was 95.24%, respectively. CONCLUSIONS: This research showed that the proposed method using three statistics features achieves good performance for glaucoma detection.