45 documents found, page 1 of 5
Integrating PET for tumour hypoxia in radiotherapy planning: Insights from Port...
Sousa, Ruben Diogo Oliveira; Faria, Brígida Mónica; Bravo, Isabel; Costa, Pedro; Costa, Pedro; Faria, Brigida MonicaIn the era of personalised medicine, tumour hypoxia (TH) is critical in radiotherapy (RT) response due to its role in tumour resistance. Positron Emission Tomography (PET) enables non-invasive assessment of TH and supports heterogeneous dose-escalation to hypoxic sub-volumes, improving treatment efficacy. This study explores Nuclear Medicine Technologists (NMT) and Radiotherapy Technologists (RTT) perceptions o...
Life cycle assessment using machine learning
Gomes, Sofia; Faria, Brígida Mónica; Oliveira, Alexandra Alves; Pinto, Edgar; Rodrigues, Matilde; Vieira, Manuela; Faria, Brigida MonicaLife Cycle Assessment (LCA) is a scientific tool that allows calculating the impact of a product or service on the environment, considering the different phases from planting to transportation, commercialization, consumption, and disposal. (1) LCA requires comprehensive data collection of the inputs and outputs such as raw materials, energy, water, used chemicals and pollutants emissions at each stage of the li...
Machine learning in tumor classification in breast cancer
Lima, Ana Sofia; Coutinho, Carolina; Machado, Raquel; Oliveira, Alexandra Alves; Faria, Brígida Mónica; Faria, Brigida Monica; Oliveira, AlexandraBreast cancer is the primary cause of mortality among women worldwide (1). Discernible patterns can be found within the disease, presenting an opportunity for the application of machine learning (ML), garnering effective results in screening and diagnosis. Different ML algorithms were tested - Decision Tree, Deep Learning (DL), k-Nearest Neighbors (k-NN) and Naïve Bayes - to construct a predictive model allowin...
Comparing time series forecasting models for health indicators: A clustering an...
Vinhal, Cláudia; Oliveira, Alexandra; Faria, Brígida; Nascimento, Ana Paula; Pimenta, Rui; Oliveira, Alexandra; Faria, Brigida Monica; Pimenta, RuiTime series are the sequence of observations ordered by equal time intervals, crucial for understanding causality, trends, and forecasts. Its analysis can be applied to several areas, such as engineering, finance, and health (1,2). One problem with the time series study is clustering, mainly understanding when two parametric time series are considered similar (3). The sum of mortality and morbidity, referred to...
Comparison of accuracy in 2D and 3D templates in total knee arthroplasty
Viana, Tânia; Faria, Brígida Mónica; Faria, Brigida MonicaTotal knee arthroplasty replaces damaged components with prostheses, often used to treat severe osteoarthritis or joint injuries. Advances such as digital templating improve preoperative planning, reducing errors and costs, but accuracy in the choice of implants is crucial to the success of the intervention. This study will compare the accuracy between three-dimensional (3D) and two-dimensional (2D) templating ...
Modelling therapeutic response in asthmatic adults: a previous exploratory anal...
Alves, Cristina; Faria, Brígida Mónica; Alves, Sandra Maria; Ferreira, Jorge; Faria, Brigida Monica; Alves, Sandra MariaAsthma is a respiratory disease characterized by chronic inflammation of the airways. Effective asthma management is essentially based on choosing the appropriate treatment for each individual (1). Data science and machine learning models offer valuable insights and enhance the outcomes achieved in asthma management (2). The main objective is to develop predictive models for therapy response in patients with as...
Predicting treatment response in wet age-relatedd macular degeneration through ...
Sousa, Vânia; Carneiro, Ângela; Faria, Brígida Mónica; Faria, Brigida MonicaWet age-related Macular Degeneration (AMD), characterized by macular neovascularization that leads to fluid leakage and retinal hemorrhage causing severe and sometimes irreversible visual damage, is one of the biggest causes of blindness in developed countries (1). Treatment with anti-vascular endothelial growth factors (anti- VEGF) has been revolutionary, but not all patients respond completely to treatment an...
In-silico prediction of the complete ataxin-3 protein network relevant for Spin...
Batista, Paulo; Vieira, Jorge; Vieira, Cristina P.; Faria, Brígida Mónica; Faria, Brigida MonicaSpinocerebellar ataxia type 3, also known as Machado Joseph disease (SCA3/MJD), is the most common inherited ataxia worldwide and is caused by a pathogenic expansion of the polyglutamine (polyQ) tract, located at the C-terminal region of the ataxin-3 protein (1). The polyQ region is involved in the stabilization of protein- protein interactions (PPIs). Abnormal polyQ expansion results in structural changes of t...
Swallowing assessment in a clinical context: artificial intelligence applications
Torres, Teresa; Faria, Brígida; Araújo, Pedro; Oliveira, Alexandra; Alves, Elisa; Faria, Brigida Monica; Oliveira, AlexandraEating and swallowing are intricate actions comprehending both voluntary and reflexive movements, engaging over thirty nerves and muscles (1). Dysphagia occurs when the normal swallowing process is compromised, increasing the risk of the swallowed material entering the larynx, and causing complications for the patient (2). Cervical auscultation (CA) is a clinical method used to evaluate the pharyngeal phase of ...
Sequence alignment: Comparative analysis of algorithms in KRAS genetic mutations
Pereira, Ana Rita; Lopes, Carlos; Oliveira, Catarina; Pereira, Gonçalo; Moreira, Rui; Faria, Brígida Mónica; Faria, Brigida MonicaFor this study a program was developed in Python on biological sequence alignment, considering the application of algorithms in the genetic analysis of Kristen rat sarcoma viral oncogene (KRAS) and its main mutations associated with cancer. The KRAS gene, like other genes in the same family, is responsible for encoding proteins that regulate cell proliferation, differentiation, and apoptosis. The algorithms emp...