Browsing by Author "Silva, Maria"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
- Knowledge discovery for risk assessment in economic and food safetyPublication . Silva, Maria; Faria, Brígida Mónica; Mónica Faria, Brígida; Reis, Luís PauloFoodborne diseases continue to spread widely in the 21st century. In Portugal, the Economic and Food Safety Authority (ASAE), have the goal of monitoring and preventing non-compliance with regulatory legislation on food safety, regulating the conduct of economic activities in the food and non-food sectors, as well as accessing and communicating risks in the food chain. This work purpose and evaluated a global risk indicator considering three risk factors provided by ASAE (non-compliance rate, product or service risk and consumption volume). It also compares the performance on the prediction of risk of four classification models Decision Tree, Naïve Bayes, k-Nearest Neighbor and Artificial Neural Network before and after feature selection and hyperparameter tuning. The principal findings revealed that the service provider, food and beverage and retail were the activity sectors present in the dataset with the highest global risk associated with them. It was also observed that the Decis ion Tree classifier presented the best results. It was also verified that data balancing using the SMOTE method led to a performance increase of about 90% with the Decision Tree and k-Nearest Neighbor models. The use of machine learning can be helpful in risk assessment related to food safety and public health. It was possible to conclude that areas regarding major global risks are the ones that are more frequented by the population and require more attention. Thus, relying on risk assessment using machine learning can have a positive influence on economic crime prevention related to food safety as well as public health.
- A low resource skeleton maturation estimation system for automatic hand X-Ray assessment in pediatric applicationsPublication . Campos, Ana; Silva, Maria; Azeredo, Ricardo; Coelho, Luis; Reis, Sara; Abreu, SílviaThe assessment of differences between skeletal age and chronological age in childhood is often based on the comparison of the patient's left hand x-ray with a reference atlas, performed by a experienced professional. This procedure involves a manual image analysis, that can be subject to inter rater variability posing several problems for clinical applications. In this paper a new methodology for skeleton maturation estimation based on automatic hand X-ray assessment for pediatric applications on a low resource devices (e.g. mobile device) is proposed. The pipeline covers hand-area estimation and bone-area estimation to achieve maturation scores which are then indexed with references images, separately for male and female. The proposed approach is based on simple image processing functions always bearing in mind the application on a mobile context. The involved steps are thoroughly presented and all the used functions are explained. The performance of the system was then evaluated using the complete pipeline. The obtained results pointed to an average error rate of 15,38±3,31%, which is subject to improvements. In particular, contrast enhancement in some lower quality images still offers some challenges.
- Mental health literacy and stigma in a municipality in the north of portugal: a cross-sectional studyPublication . Simões de Almeida, Raquel; Trigueiro, Maria João; Portugal, Paula; Sousa, Sara; Simões-Silva, Vítor; Campos, Filipa; Silva, Maria; Marques, AntónioPortugal has Europe’s second-highest prevalence of psychiatric illnesses, and this is the reason why mental health literacy (MHL) and stigma should be addressed. This study aimed to investigate the mental health literacy and stigma levels among different groups of people from Póvoa de Varzim, a municipality in the north of Portugal. Students, retired people, and professionals (education, social, and healthcare fields) were recruited using a convenience sample from June to November 2022. Participants’ MHL levels were evaluated using the Mental Health Promoting Knowledge Scale (MHPK), Mental Health Literacy Measure (MHLM) and Mental Health Knowledge Schedule (MAKS). Stigma levels were evaluated using Community Attitudes towards Mental Illness (CAMI) and the Reported and Intended Behaviour Scale (RIBS). A total of 928 questionnaires were filed. The respondents included 65.70% of women, a mean age of 43.63 (±26.71) years and 9.87 (±4.39) years of school education. MHL increased with age, education level and was higher in women (p < 0.001). A higher level of MHL was seen in health professionals (p < 0.001). Findings revealed that older people stigmatized people with mental illness more (p < 0.001), and the female gender stigmatize less (p < 0.001). In addition, results showed that stigma decreased with higher mental health literacy (r between 0.11 and 0.38; p < 0.001). To conclude, specific campaigns that promote mental health literacy should be tailored to specific profiles within this population to address those that have more stigma.