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- Automatic Classification and Segmentation of Low-Grade Gliomas in Magnetic Resonance ImagingPublication . Barbosa, Marta; Moreira, Pedro; Ribeiro, Rogério; Coelho, LuisIn this article a new methodology is proposed to tackle the problem of automatic segmentation of low-grade gliomas. The possibility of knowing the limits of this type of tumor is crucial for effectively characterizing the neoplasm, enabling, in certain cases, to obtain useful information about how to treat the patient in a more effective way. Using a database of magnetic resonance images, containing several occurrences of this type of tumors, and through a carefully designed image processing pipeline, the purpose of this work is to accurately locate, isolate and thus facilitate the classification of the pathology. The proposed methodology, described in detail, was able to achieve an accuracy of 87.5% for a binary classification task. The quality of the identified regions had an accuracy of 81.6%. These are promising results that may point the effectiveness of the approach. The low contrast of the images, as a result of the acquisition process, and the detection of very small tumors are still challenges that bring motivation to further pursue additional results.
- The use of natural language processing in palliative care research: A scoping reviewPublication . Sarmet, Max; Kabani, Aamna; Coelho, Luis; Reis, Sara Seabra dos; Zeredo, Jorge L; Mehta, Ambereen KBackground: Natural language processing has been increasingly used in palliative care research over the last 5 years for its versatility and accuracy. Aim: To evaluate and characterize natural language processing use in palliative care research, including the most commonly used natural language processing software and computational methods, data sources, trends in natural language processing use over time, and palliative care topics addressed. Design: A scoping review using the framework by Arksey and O’Malley and the updated recommendations proposed by Levac et al. was conducted. Sources: PubMed, Web of Science, Embase, Scopus, and IEEE Xplore databases were searched for palliative care studies that utilized natural language processing tools. Data on study characteristics and natural language processing instruments used were collected and relevant palliative care topics were identified. Results: 197 relevant references were identified. Of these, 82 were included after full-text review. Studies were published in 48 different journals from 2007 to 2022. The average sample size was 21,541 (median 435). Thirty-two different natural language processing software and 33 machine-learning methods were identified. Nine main sources for data processing and 15 main palliative care topics across the included studies were identified. The most frequent topic was mortality and prognosis prediction. We also identified a trend where natural language processing was frequently used in analyzing clinical serious illness conversations extracted from audio recordings. Conclusions: We found 82 papers on palliative care using natural language processing methods for a wide-range of topics and sources of data that could expand the use of this methodology. We encourage researchers to consider incorporating this cutting-edge research methodology in future studies to improve published palliative care data.
- A new equipment for automatic calibration of the Semmes-Weinstein monofilamentPublication . Castro-Martins, Pedro; Pinto-Coelho, LuisDiabetic foot is a complication that carries a considerable risk in diabetic patients. The consequent loss of protective sensitivity in the lower limbs requires an early diagnosis due to the imminent possibility of ulceration or amputation of the affected limb. To assess the loss of protective sensitivity, the 10 gf Semmes-Weinstein (SW) monofilament is the most used first-line procedure. However, the used device is most often non-calibrated and its feedback can lead to decision errors. In this paper we present an equipment that is able to automatically conduct a metrological verification and evaluation of the 10 gf SW monofilament in the assessment of the loss of protective sensitivity. Additionally, the pro posed equipment is able to simulate the practicioner’s procedure, or can be used for training purposes, providing force-feedback information. After calibration, displacement vs. buckling force contours were ploted for three distinct monofilaments, confirming then ability of the equipment to provide fast, detailed and precise information.
- Towards a pneumatic insole concept to offloading plantar pressure in diabetic foot pathologyPublication . Castro-Martins, Pedro; Pinto-Coelho, Luis; Vaz, Mário; Marques, ArcelinaDiabetic foot is a serious complication of diabetes that affects millions of people worldwide. It is characterized by poor circulation, nerve damage and high plantar pressure that can lead to the development of foot ulcers and amputations. Offloading plantar pressure in certain regions is extremely important. In this paper we propose a preliminary methodology for a new concept of a pneumatic insole to offloading pressure on critical points in the plantar region of the diabetic foot. It is expected that this pneumatic insole will have an intelligent and differentiated performance in result of the pressures imposed inside the shoe. The proposed methodology consists of producing an insole with pockets, located in critical regions of the foot, which can be inflated with air to maintain a stable pressure. If any region is identified with a pressure above the defined threshold, these pockets can empty until the pressure is uniform. This pneumatic insole will promote a better redistribution of plantar pressure in the diabetic foot, it does not add significant weight or volume to the shoe and should bring greater comfort to the user.
- Emerging advancements for virtual and augmented reality in healthcarePublication . Coelho, Luis; Queirós, Ricardo; Reis, Sara SeabraWithin the last few years, devices that are increasingly capable of offering an immersive experience close to reality have emerged. As devices decrease in size, the interest and application possibilities for them increase. In the healthcare sector, there is an enormous potential for virtual reality development, as this technology allows, on the one hand, the execution of operations or processes at a distance, decoupling realities; and on the other hand, it offers the possibility of simulation for training purposes, whenever there are contexts of risk to the patient or to the health professional. However, virtual reality devices and immersion in virtual environments still requires some improvement as complaints such as headaches and nausea are still common among users, and so continuous research and development is critical to progress the technology. Emerging Advancements for Virtual and Augmented Reality in Healthcare synthesizes the trends, best practices, methodologies, languages, and tools used to implement virtual reality and create a positive user experience while also discussing how to implement virtual reality into day-to-day work with a focus on healthcare professionals and related areas. The application possibilities and their impact are transversal to all areas of health and fields such as education, training, surgery, pain management, physical rehabilitation, stroke rehabilitation, phobia therapy, and telemedicine. Covering topics such as mental health treatment and virtual simulations, it is ideal for medical professionals, engineers, computer scientists, researchers, practitioners, managers, academicians, teachers, and students.
- A New Concept of Jig Rotary Holder System for 3-Axis CNC Milling Machine Operated by the Main Machine ControlPublication . Silva, Francisco J. G.; Campilho, R.D.S.G.; Sousa, Vitor F. C.; Coelho, Luis F. P.; Pinto Ferreira, Luís; Pereira, Maria Teresa; Matos, J.This study aims to develop a new jig holding system that is able to be controlled by a Computer Numeric Control (CNC) installed on three-axis machining centers, which can drastically improve the productivity in machining operations, enabling the machining of unparallel plans in the same setup. An action research methodology was adopted for this work, which, through a practical approach, intends to generate transferrable knowledge to other organizations whose situations are like those in this study. Together, the practical actions and the knowledge acquired create the changes needed for improving these processes. By conducting a case study, it was observed that savings of about 40 % can be easily achieved for parts with low geometric complexity. If the complexity of the parts increases, it is expected that these savings can be even higher. The return of investment is less than 2 years, which is usually affordable for enterprises. Through this study, it was possible to develop a new jig holding system that can be attached to a three-axis CNC machining center and clearly expands its functions and productivity. With this system, it is possible to work in different planes of the part in sequence, as well as use a double-sided table for the jigs, doubling the production batch each time the machine is loaded. Moreover, a list of key settings has been created with the main requirements and recommendations to adopt this kind of production system, which can be highlighted as the main research output.
- The importance of ethical reasoning in next generation tech educationPublication . Reis, Sara; Coelho, Luis; Sarmet, Max; Araújo, Joana; Corchado, Juan M.Artificial intelligence (AI) is having a profound impact on human life, with both benefits and drawbacks in the societal, environmental, and technological realms. However, the ethical implications of AI are often not addressed in technology education, leaving future professionals with a lack of awareness in this area. This is concerning, as AI has the potential to greatly information delivery and affect human thinking, interaction, decision-making, and communication. To address these issues, there is a need for a framework to guide and help future AI developers make ethically responsible decisions. In this paper we propose a framework to foster ethical awareness and promote respect for human dignity and well-being, while also preventing harm. It is designed to be incorporated into technology education, ensuring that future professionals are equipped to navigate the ethical implications of AI. By prioritizing ethical reasoning in technology education, we can build a better and more responsible AI industry, ensuring that AI can provide benefits for society and does not cause harm. Additionally, a tech industry that values ethics and social responsibility will be better equipped to build technology that serves the public interest, rather than solely maximizing profits. Teaching ethical reasoning in technology education is a crucial step in preparing future professionals to make informed and ethical decisions in the development and use of AI systems. It will lead to a better and more responsible AI industry that benefits all of society.
- 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.
- Adaptive modeling and high quality spectral estimation for speech enhancementPublication . Coelho, Luis; Braga, DanielaIn this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.
- Smart computer-assisted teaching: an innovative approach to personalized educationPublication . Coelho, Luis; Reis, Sara SeabraSmart Computer-Assisted Teaching (SCAT) has emerged as a response to the challenges of traditional classroom teaching, which can often be rigid, one-size-fits-all, and unable to accommodate the unique needs and learning styles of individual students. With the rapid advancements in technology, especially in artificial intelligence (AI) and machine learning (ML), educators and researchers have recognized the potential of using intelligent computer systems to augment and enhance traditional teaching methods. SCAT leverages these technological innovations to provide students with personalized and adaptive learning experiences. The key benefits of smart computer-assisted teaching are the possibility of personalization, fast feedback and assessment, and enhanced collaboration. AI and ML algorithms can be used to analyze student data, identify their individual learning needs, and provide targeted feedback and support. These systems are designed to adapt to the pace and style of learning of each student and provide them with personalized learning pathways that are tailored to their needs and abilities. SCAT has the potential to transform the way we educate students, providing them with more personalized and effective learning experiences that can help them to achieve their full potential and can better prepare students for the demands of the 21st century.