Browsing by Author "Oliveira, Tiago"
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- BLUECOM+: Cost-effective broadband communications at remote ocean areasPublication . Campos, Rui; Oliveira, Tiago; Cruz, Nuno; Matos, Anibal; Almeida, José MiguelThe ocean and the Blue Economy are increasingly top priorities worldwide. The immense ocean territory in the planet and its huge associated economical potential is envisioned to increase the activity at the ocean in the forthcoming years. The support of these activities, and the convergence to the Internet of Things paradigm, will demand wireless and mobile communications to connect humans and systems at remote ocean areas. Currently, there is no communications solution enabling cost-effective broadband Internet access at remote ocean areas in alternative to expensive, narrowband satellite communications. This paper presents the maritime communications solution being developed in the BLUECOM+ project. The BLUE-COM+ solution enables cost-effective broadband Internet access at remote ocean areas using standard wireless access technologies, e.g., GPRS/UMTS/LTE and Wi-Fi. Its novelty lies on the joint use of TV white spaces for long range radio communications, tethered balloons for lifting communications nodes high above the ocean surface, multi-hop relaying techniques for radio range extension, and standard access networks at the ocean. Simulation results prove it is possible to reach radio ranges beyond 100 km and bitrates in excess of 3 Mbit/s using a two-hop land-sea communications chain.
- Improving Mobile-Based Cervical Cytology Screening: A Deep Learning Nucleus-Based Approach for Lesion DetectionPublication . Mosiichuk, Vladyslav; Sampaio, Ana; Viana, Paula; Oliveira, Tiago; Rosado, LuísLiquid-based cytology (LBC) plays a crucial role in the effective early detection of cervical cancer, contributing to substantially decreasing mortality rates. However, the visual examination of microscopic slides is a challenging, time-consuming, and ambiguous task. Shortages of specialized staff and equipment are increasing the interest in developing artificial intelligence (AI)-powered portable solutions to support screening programs. This paper presents a novel approach based on a RetinaNet model with a ResNet50 backbone to detect the nuclei of cervical lesions on mobile-acquired microscopic images of cytology samples, stratifying the lesions according to The Bethesda System (TBS) guidelines. This work was supported by a new dataset of images from LBC samples digitalized with a portable smartphone-based microscope, encompassing nucleus annotations of 31,698 normal squamous cells and 1395 lesions. Several experiments were conducted to optimize the model’s detection performance, namely hyperparameter tuning, transfer learning, detected class adjustments, and per-class score threshold optimization. The proposed nucleus-based methodology improved the best baseline reported in the literature for detecting cervical lesions on microscopic images exclusively acquired with mobile devices coupled to the μSmartScope prototype, with per-class average precision, recall, and F1 scores up to 17.6%, 22.9%, and 16.0%, respectively. Performance improvements were obtained by transferring knowledge from networks pre-trained on a smaller dataset closer to the target application domain, as well as including normal squamous nuclei as a class detected by the model. Per-class tuning of the score threshold also allowed us to obtain a model more suitable to support screening procedures, achieving F1 score improvements in most TBS classes. While further improvements are still required to use the proposed approach in a clinical context, this work reinforces the potential of using AI-powered mobile-based solutions to support cervical cancer screening. Such solutions can significantly impact screening programs worldwide, particularly in areas with limited access and restricted healthcare resources.
- Polimedicação em doentes em programa de reabilitação cardíacaPublication . Oliveira, Tiago; Silva, Nuno; Oliveira, Ana Isabel; Pinho, Cláudia; Ferraz Oliveira, RitaPolimedicação consiste na utilização de cinco ou mais medicamentos. Programas de Reabilitação Cardíaca (PRC) permitem otimizar a recuperação funcional do doente que sofreu um acidente cardiovascular, melhorar a qualidade de vida e reduzir o risco de complicações.