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- Towards an Effective Decision Support System for Diabetic Foot Ulcers Diagnostic and Treatment AssessmentPublication . Ricardo Vardasca, PhD, ASIS, FRPS; Martinho, DomingosDiabetes mellitus (DM) is a fast-growing metabolic condition that threatens human population quality of living in the overcoming decades. One of its severe consequences is diabetic foot ulcers (DFU), which affect up to a quarter of the DM patients in their lifetime. This consequence leads to high health costs and significant decrease of the patients’ quality of life and self-esteem. In order to cope with the rising demands of heath resources and shortage in clinical human assets intelligent computational tools are required to aid in the decision where a patient is in an early stage of a DFU development and on the appraisal of a DFU treatment. It is aim of this research to provide a critical overview of the existing decision support systems (DSS) and publicly available research datasets for diabetic foot ulcers early diagnosis and treatment assessment, and thus proposing a new infrastructure system to deal with it overcoming the past attempts. The existing DFU DSS failed in being introduced in clinical practice due to total discrepancy with current daily clinical practice with DFU and the publicly available DM research datasets are shorter in data for feeding a new DSS. This research presents the actual and promising future data required for effective decisions and discloses a proposed architecture for a DSS applicable to DFU early diagnosis and treatment evaluation. Implementing the proposed system will take time but it will definitely contribute to cope with the patient demands, associated cost reduction and promotion of patients care.
- Infrared Thermal Imaging: A dataset definition towards decision making and intelligencePublication . Ricardo Vardasca, PhD, ASIS, FRPS; Bento, Fernando; TERESO, MARCO; Martinho, DomingosInfrared imaging is being used every day for monitoring and diagnostic purposes, although it is poorly documented, which can be a major barrier for intelligence creation from the data collected. This research looked deeper into reference recent literature to find the different sources of data related to an IR examination. It was found that exam, image, object of interest, environmental and equipment data are required for a comprehensive dataset. This dataset will enforce quality assurance and drive decision making through being the basis for intelligence generation.
- Towards Portuguese Sign Language Identification Using Deep LearningPublication . Ricardo Vardasca, PhD, ASIS, FRPS; Martinho, DomingosIn Portugal there are above 80,000 people with hearing impairment with the need to communicate through the sign language. Equal opportunities and social inclusion are the major concerns of the current society. It is aim of this research to create and evaluate a Deep Learning model that using a dataset with images of characters in Portuguese sign language can identify the gesture of a user, recognizing it. For model training, 5826 representative samples of the characters ‘C’, ‘I’, ‘L’, ‘U’ and ‘Y’ in Portuguese sign language. The Deep Learning model is based on a convolutional neural network. The model evaluated using the sample allowed for an accuracy of 98.5%, which is considered as a satisfactory result. However, there are two gaps: the existence of datasets with the totality of the alphabet in the Portuguese sign language and with the various representations of movement that each word has at the layout of letters. Using the proposed model with more complete datasets would allow to develop more inclusive user interfaces and equal opportunities for users with auditory difficulties.
- Teaching Sentiment in Emergency Online Learning—A Conceptual ModelPublication . Ricardo Vardasca, PhD, ASIS, FRPS; Martinho, Domingos; Sobreiro, PedroDue to the COVID-19 pandemic, higher education institutions with a face-to-face model have found themselves in the contingency of migrating to online learning. This study explores the perspective of all the lecturers at a Portuguese private higher education institution who were invited to participate, regardless of their research area, in this questionnaire. It aims to propose and test a conceptual model that combines attitudes, preferred activities, and technological experience with the sentiment about the impact of this experience on students’ learning process, on their teaching activity, and on the strategy of higher education institutions. An online questionnaire was conducted to 65 lecturers engaging in emergency online lecturing. The obtained results showed that lecturers reveal a positive attitude towards online lecturing, tend to prefer activities in which they feel most comfortable in face-to-face lecturing, and consider having technological experience useful for online activities. Lecturers have a positive sentiment about the impact of online learning on students’ learning, their faculty career, and the strategy of higher education institutions. The proposed conceptual model test shows that the model has well-fitting conditions. The results confirm the hypotheses formulated: namely, the predictive effect of attitude, preferred activities, and technological experience on sentiment. Faculty engagement in emergency online lecturing shows that the members are available to participate in the changing process, and the proposed conceptual model can be used to assess this readiness.
- Towards an Effective Decision Support System for Diabetic Foot Ulcers Diagnostic and Treatment AssessmentPublication . Ricardo Vardasca, PhD, ASIS, FRPS; Martinho, DomingosDiabetes mellitus (DM) is a fast-growing metabolic condition that threatens human population quality of living in the overcoming decades. One of its severe consequences is diabetic foot ulcers (DFU), which affect up to a quarter of the DM patients in their lifetime. This consequence leads to high health costs and significant decrease of the patients’ quality of life and self-esteem. In order to cope with the rising demands of heath resources and shortage in clinical human assets intelligent computational tools are required to aid in the decision where a patient is in an early stage of a DFU development and on the appraisal of a DFU treatment. It is aim of this research to provide a critical overview of the existing decision support systems (DSS) and publicly available research datasets for diabetic foot ulcers early diagnosis and treatment assessment, and thus proposing a new infrastructure system to deal with it overcoming the past attempts. The existing DFU DSS failed in being introduced in clinical practice due to total discrepancy with current daily clinical practice with DFU and the publicly available DM research datasets are shorter in data for feeding a new DSS. This research presents the actual and promising future data required for effective decisions and discloses a proposed architecture for a DSS applicable to DFU early diagnosis and treatment evaluation. Implementing the proposed system will take time but it will definitely contribute to cope with the patient demands, associated cost reduction and promotion of patients care.
- Easy-Programming: towards a web collaborating algorithmic and programming aid for early apprenticesPublication . Ricardo Vardasca, PhD, ASIS, FRPS; TERESO, MARCO; Bento, Fernando; Martinho, DomingosScience, Technology, Engineering and Mathematics (STEM) under graduate students must develop problem solving skills through algorithmic and programming learning. There are several tools available to aid them in this pro cess but none in a web collaborative environment that can be used for e learning accommodating the three methods available for that development: code, flowchart, and pseudocode. It is aim of this research to outline the exist ing tools and their features, and to propose a new web based collaborative tool accommodating the main features found. An architecture, technological infra structure, database structure, requirements definition, UML use case and class diagrams and a user interface were proposed. New STEM undergraduate stu dents can develop a solid foundation in algorithmic thinking, problem-solving skills, and the ability to effectively communicate and collaborate with others, establishing the foundations for their success in specific fields.