polito.it
Politecnico di Torino (logo)

Methods for Removing Non-Interesting Itemsets when Mining Electronic Healthcare Records

Genna, Vincenzo

Methods for Removing Non-Interesting Itemsets when Mining Electronic Healthcare Records.

Rel. Silvia Anna Chiusano, Ricard GavaldÃ. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2018

[img]
Preview
PDF (Tesi_di_laurea) - Tesi
Accesso al documento: Accesso libero
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview
Abstract:

The usage of data mining techniques in healthcare has exponentially increased in the last years. Analyzing the huge amount of data that is nowadays produced by healthcare systems can lead to the extraction of useful and interesting informations about patients and diseases, which can be exploited to improve medical research and knowledge. Understanding how diseases and other characteristics of a patient are interrelated is a crucial point because it can help healthcare specialists to focus only on important factors when addressing cures for a given clinical case. Frequent itemset mining techniques are widely used for this purpose, but they can lead to the retrieval of too many redundant or not interesting pieces of information. In this project we study and report performances of a measure proposed to remove redundant and irrelevant rules from data and suggest an approach to unveil the main comorbidities for a given disease, along with the possibility to use the latter results to further filter not interesting informations. Results show the effectiveness of the two studied methods as also proved by the main literature that was reviewed during the project, even if we suggest the collaboration with healthcare specialists in order to get more relevant outcomes.

Relatori: Silvia Anna Chiusano, Ricard GavaldÃ
Anno accademico: 2018/19
Tipo di pubblicazione: Elettronica
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA
Ente in cotutela: UPC - FIB - Universitat Politecnica de Catalunya (SPAGNA)
Aziende collaboratrici: NON SPECIFICATO
URI: http://webthesis.biblio.polito.it/id/eprint/9058
Modifica (riservato agli operatori) Modifica (riservato agli operatori)