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II. Componente Politécnica

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http://hdl.handle.net/10400.1/2

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Percorrer II. Componente Politécnica por Objetivos de Desenvolvimento Sustentável (ODS) "10:Reduzir as Desigualdades"

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  • PneumoNet: artificial intelligence assistance for pneumonia detection on X-rays
    Publication . Antunes, Carlos; Rodrigues, Joao; Cunha, António
    Pneumonia is a respiratory condition caused by various microorganisms, including bacteria, viruses, fungi, and parasites. It manifests with symptoms such as coughing, chest pain, fever, breathing difficulties, and fatigue. Early and accurate detection is crucial for effective treatment, yet traditional diagnostic methods often fall short in reliability and speed. Chest X-rays have become widely used for detecting pneumonia; however, current approaches still struggle with achieving high accuracy and interpretability, leaving room for improvement. PneumoNet, an artificial intelligence assistant for X-ray pneumonia detection, is proposed in this work. The framework comprises (a) a new deep learning-based classification model for the detection of pneumonia, which expands on the AlexNet backbone for feature extraction in X-ray images and a new head in its final layers that is tailored for (X-ray) pneumonia classification. (b) GPT-Neo, a large language model, which is used to integrate the results and produce medical reports. The classification model is trained and evaluated on three publicly available datasets to ensure robustness and generalisability. Using multiple datasets mitigates biases from single-source data, addresses variations in patient demographics, and allows for meaningful performance comparisons with prior research. PneumoNet classifier achieves accuracy rates between 96.70% and 98.70% in those datasets.
    2025-07-07Artigo científico Acesso aberto Ver mais
  • Resident empowerment in all-inclusive context: cost–benefit perception and support for sustainable tourism development in a small island destination
    Publication . Santos, Edson Redy Moreira dos; Nobre Pereira, Luis; Pinto, Patrícia; Ribeiro, Manuel Alector
    This study examines the relationships among resident empowerment, perceptions of tourism costs and benefits, and support for sustainable tourism development (SSTD) in a small island destination dominated by all-inclusive resorts. Using survey data from 341 residents in Cape Verde and employing PLS-SEM analysis, results reveal significant relationships between empowerment, benefits, and SSTD. The perception of all-inclusive resorts' positive impacts moderates the relationship between empowerment and SSTD, while the perception of all-inclusive resorts' costs does not moderate any relationships. The study contributes to understanding how all-inclusive tourism development influences resident attitudes and support for sustainability in small island contexts. The findings underscore the importance of empowering residents and managing perceptions of tourism impacts to foster SSTD. Practical implications include the need for policies that promote local empowerment, equitable benefit distribution, and mitigation of negative impacts to ensure long-term sustainability of small island destinations and beyond.
    2025-12-22Artigo científico Acesso aberto Ver mais