| Titre : | Heart attack prediction based on machine learning techniques | | Type de document : | document multimédia | | Auteurs : | Soumia Abdelaziz, Auteur ; Chaima Ferroudj, Auteur ; Mustapha Bouakkaz, Directeur de thèse | | Editeur : | Laghouat : Université Amar Telidji - Département d'informatique | | Année de publication : | 2024 | | Importance : | 42 p. | | Accompagnement : | 1 disque optique numérique (CD-ROM) | | Note générale : | Option : Systèmes d’information et de décision | | Langues : | Anglais | | Mots-clés : | Machine learning SVM Logistic Regression MLPClassifier | | Résumé : | The emergence of artificial intelligence and its rapid spread has led to a change in many factors, especially in the medical field, so that it has an effective role in exploring diseases, methods of diagnosis, and assisting in health care in various forms. One of the common diseases that pose a great risk to human health is heart disease, especially heart attacks. Many machine learning models have treated heart diseases in general or heart attacks in particular, but with different models. In this thesis, we wanted to experiment with machine learning techniques, especially classification, to classify a person’s condition as either having the possibility of a heart attack or not having any possibility of it occurring. So we used logistic regression, SVM and ANN to try to reach the highest possible accuracy to provide Greater effectiveness when using these models. To facilitate the use of these models, we have developed a simple website using Flask that enables the user to enter the necessary factors to predict a heart attack. | | note de thèses : | Mémoire de master en informatique |
Heart attack prediction based on machine learning techniques [document multimédia] / Soumia Abdelaziz, Auteur ; Chaima Ferroudj, Auteur ; Mustapha Bouakkaz, Directeur de thèse . - Laghouat : Université Amar Telidji - Département d'informatique, 2024 . - 42 p. + 1 disque optique numérique (CD-ROM). Option : Systèmes d’information et de décision Langues : Anglais | Mots-clés : | Machine learning SVM Logistic Regression MLPClassifier | | Résumé : | The emergence of artificial intelligence and its rapid spread has led to a change in many factors, especially in the medical field, so that it has an effective role in exploring diseases, methods of diagnosis, and assisting in health care in various forms. One of the common diseases that pose a great risk to human health is heart disease, especially heart attacks. Many machine learning models have treated heart diseases in general or heart attacks in particular, but with different models. In this thesis, we wanted to experiment with machine learning techniques, especially classification, to classify a person’s condition as either having the possibility of a heart attack or not having any possibility of it occurring. So we used logistic regression, SVM and ANN to try to reach the highest possible accuracy to provide Greater effectiveness when using these models. To facilitate the use of these models, we have developed a simple website using Flask that enables the user to enter the necessary factors to predict a heart attack. | | note de thèses : | Mémoire de master en informatique |
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Heart attack prediction based on machine learning techniques
