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- Evaluating Intelligent Methods for Decision Making Support in Dermoscopy Based on Information Gain and EnsemblePublication . Spolaôr, Newton; Fonseca-Pinto, Rui; Mendes, Ana I.; Ensina, Leandro A.; Takaki, Weber S. R.; Parmezan, Antonio R. S.; Nogueira, Conceição V.; Coy, Claudio S. R.; Wu, Feng C.; Lee, Huei D.Melanoma, the most dangerous skin cancer, is sometimes associated with a nevus, a relatively common skin lesion. To find early melanoma, nevus, and other lesions, dermoscopy is often used. In this context, intelligent methods have been applied in dermoscopic images to support decision making. A typical computer-aided diagnosis method comprises three steps: (1) extraction of features that describe image properties, (2) selection of important features previously extracted, (3) classification of images based on the selected features. In this work, traditional data mining approaches underexploited in dermoscopy were applied: information gain for feature selection and an ensemble classification method based on gradient boosting. The former technique ranks image features according to data entropy, while the latter combines the outputs of single classifiers to predict the image class. After evaluating these approaches in a public dataset, we can observe that the results obtained are competitive with the state-of-the-art. Moreover, the presented approach allows a reduction of the total number of features and types of features to produce similar classification scores.
- Pulse transit time estimation for continuous blood pressure measurement: a comparative studyPublication . Duarte, Diana; Lopes, Nuno Vieira; Fonseca-Pinto, Rui
- Tracking human routines towards adaptive monitoring: the MOVIDA.domus platformPublication . Gordalina, Gonçalo; Figueiredo, João; Martinho, Ricardo; Rijo, Rui; Correia, Pedro; Assunção, Pedro A. Amado; Seco, Alexandra; Pires, Gabriel; Oliveira, Luís; Fonseca-Pinto, RuiAccording to estimates by the World Health Organization, the average life expectancy will continue to rise. This indicator, being a measure of success in terms of healthcare, is not synonymous with quality of life and will increase healthcare costs. Associated with this problem are also the changes in terms of the organization of society, which has not been able to solve these constraints of functional limitations, dementia, social isolation, and loneliness. This paper presents the concept of adaptive surveillance based on mobile technology and artificial intelligence, presented in the context of a global physical activity monitoring program (MOVIDA), in his domus dimension designed to the elderly people with some functional limitation or dementia. The proposed solution for an adaptive surveillance is thus to conduct direct supervision programs, to enroll persons who live alone or in nursing homes who need supervision without limiting their individual autonomy. The preliminary results show that it is possible to use the data obtained from a mobile smartphone to identify routines and use this information to identify daily patterns. Changes to these routine patterns can be used to generate alarms for caregivers.
- Classification of reticular pattern and streaks in dermoscopic images based on texture analysisPublication . Machado, Marlene; Pereira, Jorge; Fonseca-Pinto, RuiThe early detection of melanoma is one of the greatest challenges in clinical practice of dermatology, and the reticular pattern is one of the most important dermoscopic structures to improve melanocytic lesion diagnosis. A texture-based approach is developed for the automatic detection of reticular patterns, whose output will assist clinical decision-making. Feature selection was based on the use of two algorithms by means of the classical graylevel co-occurrence matrix and Laws energy masks optimized on a set of 104 dermoscopy images. The AdaBoost (adaptive boosting) approach to machine learning was used within this strategy. Results suggest superiority of LEM for reticular pattern detection in dermoscopic images, achieving a sensitivity of 90.16% and a specificity of 86.67%. The use of automatic classification in dermoscopy to support clinicians is a strong tool to assist diagnosis; however, the use of automatic classification as a complementary tool in clinical routine requires algorithms with high levels of sensitivity and specificity. The results presented in this work will contribute to achieving this goal.
- CBmeter study: Protocol for assessing the predictive value of peripheral chemoreceptor overactivation for metabolic diseasesPublication . Lages, Marlene; Carvalho, Lucinda; Feijó, Salvato; Vieira, Alexandra; Fonseca-Pinto, Rui; Guarino, Maria PedroEarly screening of metabolic diseases is crucial since continued undiagnostic places an ever-increasing burden on healthcare systems. Recent studies suggest a link between overactivated carotid bodies (CB) and the genesis of type 2 diabetes mellitus. The non-invasive assessment of CB activity by measuring ventilatory, cardiac and metabolic responses to challenge tests may have predictive value for metabolic diseases; however, there are no commercially available devices that assess CB activity. The findings of the CBmeter study will clarify the role of the CBs in the genesis of—metabolic diseases and guide the development of new therapeutic approaches for early intervention in metabolic disturbances. Results may also contribute to patient classification and stratification for future CB modulatory interventions.
- Screening of obstructive sleep apnea using Hilbert–Huang decomposition of oronasal airway pressure recordingsPublication . Caseiro, P.; Fonseca-Pinto, Rui; Andrade, A.Polysomnographic signals are usually recorded from patients exhibiting symptoms related to sleep disorders such as obstructive sleep apnea (OSA). Analysis of polysomnographic data allows for the determination of the type and severity of sleep apnea or other sleep-related disorders by a specialist or technician. The usual procedure entails an overnight recording several hours long. This paper presents a methodology to help with the screening of OSA using a 5-min oronasal airway pressure signal emanating from a polysomnographic recording during the awake period, eschewing the need for an overnight recording. The clinical sample consisted of a total of 41 subjects, 20 non-OSA individuals and 21 individuals with OSA. A signal analysis technique based on the Hilbert-Huang transform was used to extract intrinsic oscillatory modes from the signals. The frequency distribution of both the first mode and second mode and their sum were shown to differ significantly between non-OSA subjects and OSA patients. An index measure based on the distribution frequencies of the oscillatory modes yielded a sensitivity of 81.0% (for 95% specificity) for the detection of OSA. Two other index measures based on the relation between the area and the maximum of the 1st and 2nd halves of the frequency histogram both yielded a sensitivity of 76.2% (for 95% specificity). Although further tests will be needed to test the reproducibility of these results, the proposed measures seem to provide a fast method to screen OSA patients, thus reducing the costs and the waiting time for diagnosis.
- Dynamic laser speckle in medical imaging : on the quantification of skin patternsPublication . Bento, Lúcia; Távora, Luis; Assunção, Pedro A. Amado; Faria, Sérgio; Fonseca-Pinto, Rui
- Fine-tuning pre-trained neural networks for medical image classification in small clinical datasetsPublication . Spolaôr, Newton; Lee, Huei Diana; Mendes, Ana Isabel; Nogueira, Conceição; Parmezan, Antonio Rafael Sabino; Takaki, Weber Shoity Resende; Coy, Claudio Saddy Rodrigues; Wu, Feng Chung; Fonseca-Pinto, RuiConvolutional neural networks have been effective in several applications, arising as a promising supporting tool in a relevant Dermatology problem: skin cancer diagnosis. However, generalizing well can be difficult when little training data is available. The fine-tuning transfer learning strategy has been employed to differentiate properly malignant from non-malignant lesions in dermoscopic images. Fine-tuning a pre-trained network allows one to classify data in the target domain, occasionally with few images, using knowledge acquired in another domain. This work proposes eight fine-tuning settings based on convolutional networks previously trained on ImageNet that can be employed mainly in limited data samples to reduce overfitting risk. They differ on the architecture, the learning rate and the number of unfrozen layer blocks. We evaluated the settings in two public datasets with 104 and 200 dermoscopic images. By finding competitive configurations in small datasets, this paper illustrates that deep learning can be effective if one has only a few dozen malignant and non-malignant lesion images to study and differentiate in Dermatology. The proposal is also flexible and potentially useful for other domains. In fact, it performed satisfactorily in an assessment conducted in a larger dataset with 746 computerized tomographic images associated with the coronavirus disease.
- Literacia para a Igualdade de Género, Não Discriminação e InclusãoPublication . Oliveira, Ana Zita Lopes Baptista de; Henriques, Carolina Miguel da Graça; Sá, Cristina Isabel Branco de; Duque, Gustavo Fernando Espírito Santo Fonseca; Brasão, Inês Paulo Cordeiro; Duarte, Isabel Fernanda Lopes; Varela, Jorge Alexandre Barroca de Sousa; Frade, José José Manuel Couceiro Barosa Correia; Silva, Paulo Jorge Soares da; Pinto, Rui Manuel da FonsecaNo âmbito da implementação do Plano de Igualdade de Género, Não Discriminação e Inclusão do Instituto Politécnico de Leiria, procurou-se conhecer literacia dos dirigentes institucionais sobre a temática da igualdade de género, não discriminação e inclusão, em que o questionário se encontrava dividido por seis dimensões. Após o convite à participação dos dirigentes institucionais, num total de 33 dirigentes, participaram 13 dirigentes de forma voluntária, livre e esclarecida. Verificou-se uma baixa taxa de adesão dos dirigentes à resposta a este questionário, possivelmente por falta de sensibilização face à problemática. Observa-se ainda, pelas respostas obtidas, que são necessárias medidas e intervenções que potenciem a conscientização e os conhecimentos dos dirigentes do Instituto Politécnico de Leiria face às temáticas da Igualdade de Género, Não Discriminação e Inclusão.
- Blood pressure assessment during standard clinical manoeuvres: A noninvasive PPT based approachPublication . Duarte, Diana; Lopes, Nuno Vieira; Fonseca-Pinto, RuiContinuous and reliable blood pressure (BP) monitoring during standard clinical manoeuvres provides important information about the cardiovascular system condition. Common invasive methods are accurate but denote increased risk. An alternative approach is based on changes in pulse transit time (PTT) defined as the time delay between the R-wave of the electrocardiogram (ECG) and the peak value of the photoplethysmogram (PPG) signal at the same cardiac cycle.