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O estudo dos humanos tornando-se máquinas: Criação de uma rede neuronal artificial para prevenção do risco da doença cardiovascular
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| Documento em Acesso Embargado até dia 29-11-2026. Tente solicitar cópia ao autor carregando no ficheiro | 1.53 MB | Adobe PDF |
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Abstract(s)
Atualmente, os programas de Inteligência Artificial (IA) aplicados à medicina baseiam-se em modelos simbólicos que classificam doenças e as suas relações com os fatores do doente e as suas manifestações clínicas. Entre os sistemas mais utilizados, encontram-se softwares especializados que integram o conhecimento médico e realizam tarefas específicas, permitindo raciocinar a partir de dados dos utentes. Estes softwares procuram imitar o comportamento humano, fornecendo soluções especializadas em áreas médicas específicas.
O principal objetivo desta dissertação consiste em analisar as técnicas que em vista a melhoria da qualidade de vida das pessoas através do desenvolvimento de órgãos artificiais avançados, membros, próteses e sangue artificial. O objetivo específico pretende investigar os fatores de risco associados ao desenvolvimento de doenças cardiovascular e criar uma aplicação prática, utilizando redes neuronais artificiais através do software Matlab. Esta aplicação visa identificar a probabilidade de um indivíduo desenvolver doenças cardiovasculares, facilitando a implementação de estratégias preventivas e tratamentos personalizados.
O presente estudo incluí a utilização da rede neuronal, uma ferramenta poderosa em áreas da Ciência e da Engenharia, com foco na criação e manipulação de redes neuronais. Foram abordados comandos para operações matemáticas e análise de dados, bem como a implementação de redes neuronais com diferentes arquiteturas. Este estudo explorou também funções pré-definidas e personalizadas da rede neuronal, utilizadas para cálculos, processamento de sinais e simulação, com especial atenção para a visualização dos dados obtidos.
Os resultados basearam-se numa amostra de 121 indivíduos, maioritariamente residentes na Covilhã. A maioria dos inquiridos encontrava-se na faixa etária dos 26-35 anos e era do sexo masculino. Quanto ao peso, por um lado, cerca de 19% apresentava excesso de peso e, por outro, a maioria tinha peso normal. Cerca de metade dos participantes tinham um nível médio de conhecimento sobre doenças cardiovasculares, e a maioria não apresentava histórico familiar dessas condições. Fatores de risco, como a hipertensão, colesterol elevado e obesidade, foram comuns entre os participantes. O consumo excessivo de álcool foi reportado por 55% da amostra, enquanto 11% eram fumadores. A prática de exercício físico era irregular, e quase metade dos inquiridos consome frequentemente gorduras saturadas.
Concluiu-se que a população inquirida, maioritariamente jovem, apresenta fatores significativos para o desenvolvimento de doenças cardiovasculares. A hipertensão arterial, hipercolesterol, hábitos alcoólicos e tabágicos, sedentarismo e a ingestão insuficiente de frutas e vegetais foram os fatores identificados e considerados como os fatores mais relevantes no decorrer deste estudo. Estes resultados são cruciais para a compreensão da saúde cardiovascular dos jovens adultos.
Currently, Artificial Intelligence programs applied to medicine are based on symbolic models that classify diseases and their relationships with the patient’s factors and its clinical manifestations. Among the most used systems are specialized software that integrates medical knowledge and performs specific tasks, allowing reasoning based on user data. These software programs seek to imitate human behavior, providing specialized solutions in specific medical areas. The main objective of this dissertation is to analyse techniques that allow to improve people's quality of life through the development of advanced artificial organs, limbs, prosthetics and artificial blood. The specific objective aims to investigate the risk factors associated with the development of cardiovascular diseases and create a practical application, using artificial neural networks using Matlab software. This application aims to identify the likelihood of an individual developing cardiovascular diseases, facilitating the implementation of preventive strategies and personalized treatments. The present study includes the use of neural network, a powerful tool in areas of Science and Engineering, focusing on the creation and manipulation of neural networks. Commands for mathematical operations and data analysis were covered, as well as the implementation of neural networks with different architectures. This study also explored pre-defined and customized neural network functions, used for calculations, signal processing and simulation, with special attention to the visualization of the data obtained. The results were based on a sample of 121 individuals, mostly resident in Covilhã. The majority of respondents were in the 26-35 age group and were male. Regarding weight, on the one hand, around 19% were overweight and, on the other, the majority were of normal weight. About half of the participants had an average level of knowledge about cardiovascular diseases, and the majority had no family history of these conditions. Risk factors, such as hypertension, high cholesterol and obesity, were common among the participants. Excessive alcohol consumption was reported by 55% of the sample, while 11% were smokers. Physical exercise was irregular, and almost half of those surveyed frequently consumed saturated fats. It is concluded that the respondent population, mostly young, presents significant factors for the development of cardiovascular diseases. Arterial hypertension, hypercholesterolemia, alcohol and smoking habits, physical inactivity and insufficient intake of fruits and vegetables were the factors identified and considered as the most relevant factors during this study. These results are crucial for understanding the cardiovascular health of young adults.
Currently, Artificial Intelligence programs applied to medicine are based on symbolic models that classify diseases and their relationships with the patient’s factors and its clinical manifestations. Among the most used systems are specialized software that integrates medical knowledge and performs specific tasks, allowing reasoning based on user data. These software programs seek to imitate human behavior, providing specialized solutions in specific medical areas. The main objective of this dissertation is to analyse techniques that allow to improve people's quality of life through the development of advanced artificial organs, limbs, prosthetics and artificial blood. The specific objective aims to investigate the risk factors associated with the development of cardiovascular diseases and create a practical application, using artificial neural networks using Matlab software. This application aims to identify the likelihood of an individual developing cardiovascular diseases, facilitating the implementation of preventive strategies and personalized treatments. The present study includes the use of neural network, a powerful tool in areas of Science and Engineering, focusing on the creation and manipulation of neural networks. Commands for mathematical operations and data analysis were covered, as well as the implementation of neural networks with different architectures. This study also explored pre-defined and customized neural network functions, used for calculations, signal processing and simulation, with special attention to the visualization of the data obtained. The results were based on a sample of 121 individuals, mostly resident in Covilhã. The majority of respondents were in the 26-35 age group and were male. Regarding weight, on the one hand, around 19% were overweight and, on the other, the majority were of normal weight. About half of the participants had an average level of knowledge about cardiovascular diseases, and the majority had no family history of these conditions. Risk factors, such as hypertension, high cholesterol and obesity, were common among the participants. Excessive alcohol consumption was reported by 55% of the sample, while 11% were smokers. Physical exercise was irregular, and almost half of those surveyed frequently consumed saturated fats. It is concluded that the respondent population, mostly young, presents significant factors for the development of cardiovascular diseases. Arterial hypertension, hypercholesterolemia, alcohol and smoking habits, physical inactivity and insufficient intake of fruits and vegetables were the factors identified and considered as the most relevant factors during this study. These results are crucial for understanding the cardiovascular health of young adults.
Description
Keywords
Inteligência Artificial Rede Neuronal Fatores de Risco Doença Cardiovascular Coração Fígado Implante Pâncreas Artéria Órgão Artificial Transplante de Órgão Artificial Intelligence Neuronal Network Risk Factors