Diabetes diagnonis using machine learning
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Keywords
Diabetes diagnosis ; PIMA Indians dataset ; Supervised machine learning category ; Διάγνωση διαβήτη ; Επιβλεπόμενη μηχανική μάθησηAbstract
The increase of technology and data science has provided significant development in the field of medicine and even more in the prediction of diseases for their timely and effective treatment.
The present thesis aims to study diabetes diagnosis using machine learning techniques. More specifically, it is a study focuses on comparing machine learning algorithms as to conclude to the one that provide the most accurate prediction.
For this purpose, a database widely known in the scientific bibliography for the prediction of diabetes was used, the Pima Indians Diabetes database, which contains data and measurements that help detect type 2 diabetes.
Using the abovementioned database, modeling phase is performed with a number of appropriate algorithms and calculation of sufficient evaluation measures aiming to find out the optimal prediction algorithm.
Postgraduate Studies Programme
Πληροφοριακά Συστήματα και ΥπηρεσίεςDepartment
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών ΣυστημάτωνNumber of pages
86Language
EnglishCollections
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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα