AIMC Topic: Portugal

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Gilthead sea bream gut bacteriome as a valuable tool for seafood provenance analysis.

Applied and environmental microbiology
The increasing demand for high-quality seafood underscores the significant challenges posed by rampant seafood fraud. This study aimed to identify regional capture biomarkers by using the gut bacteriome of specimens through state-of-the-art long-rea...

An intelligent community-based system for healthcare prioritisation.

Scientific reports
Healthcare rationing is unavoidable in systems constrained by limited resources. While decisions about who should be treated are ethically complex, they must reflect not only efficiency concerns but also socially accepted values. This study aims to d...

Artificial intelligence in the prescription of acute medical treatments in primary healthcare - comparison of the performance of family physicians and ChatGPT.

BMC primary care
INTRODUCTION: Artificial intelligence (AI) is increasingly being recognized as a transformative force in healthcare, showing significant promise in supporting healthcare professionals. AI has many applications in healthcare, including providing real-...

Statistical and machine learning models for predicting university dropout and scholarship impact.

PloS one
Although student dropout is an inevitable aspect of university enrollment, when analyzed, universities can gather information which enables them to take preventative actions that mitigate dropout risk. We study a data set consisting of 4,424 records ...

Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal.

PloS one
This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using only self-reported survey data. Such a model could enable scalable and cost-effective screening and ta...

Health Care Professionals and Data Scientists' Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study.

Journal of medical Internet research
BACKGROUND: Heart failure (HF) is a significant global health problem, affecting approximately 64.34 million people worldwide. The worsening of HF, also known as HF decompensation, is a major factor behind hospitalizations, contributing to substantia...

Enhancing prediction of major depressive disorder onset in adolescents: A machine learning approach.

Journal of psychiatric research
Major Depressive Disorder (MDD) is a prevalent mental health condition that often begins in adolescence, with significant long-term implications. Indicated prevention programs targeting adolescents with mild symptoms have shown efficacy, yet the meth...

MediAlbertina: An European Portuguese medical language model.

Computers in biology and medicine
BACKGROUND: Patient medical information often exists in unstructured text containing abbreviations and acronyms deemed essential to conserve time and space but posing challenges for automated interpretation. Leveraging the efficacy of Transformers in...

Quality of science journalism in the age of Artificial Intelligence explored with a mixed methodology.

PloS one
Science journalists, traditionally, play a key role in delivering science information to a wider audience. However, changes in the media ecosystem and the science-media relationship are posing challenges to reliable news production. Additionally, rec...

Machine learning models' assessment: trust and performance.

Medical & biological engineering & computing
The common black box nature of machine learning models is an obstacle to their application in health care context. Their widespread application is limited by a significant "lack of trust." So, the main goal of this work is the development of an evalu...