Abstracts

Scientific search strategies optimization using artificial intelligence techniques

by Daniel Mauricio Nieto González

This project designed and implemented a functional software prototype, capable of optimizing the process and results of search strategies and the selection of articles when preparing a medical systematic review. The application used artificial intelligence for decision-making support in the most critical phases of the process. It was possible to suggest which articles to include or exclude, using a Naive Bayes model that managed to classify the manuscripts with 79.66% precision, and an AUC of 91.13% based on previous classifications made by the user. A TF-IDF algorithm regularized with L2, and natural language processing including stemming, was used for information extraction. It was also possible to suggest which keywords to include or exclude with the TD-IDF algorithm. When comparing the results with the metrics of other tools, the AUC and accuracies were good. For the architectural design, the RNF and RF were identified, the ADD and ATAM methodologies were also used, developing 4 + 1 views, which allowed the design and implementation of a client-server architecture with a layered server, where the artificial intelligence module it was deployed as a backend server in one of the 4 applications built. The best security practices such as encryption, whitelisting and use of JWT tokens were included. The architecture built used services of the AWS Cloud infrastructure such as DynamoDB, S3 Buckets and RDS Postgres which altogether to the RESTful design of the applications permitted a high scalability. @font-face {font-family:"Cambria Math"; panose-1:2 4 5 3 5 4 6 3 2 4; mso-font-charset:0; mso-generic-font-family:roman; mso-font-pitch:variable; mso-font-signature:-536870145 1107305727 0 0 415 0;}p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-unhide:no; mso-style-qformat:yes; mso-style-parent:""; margin:0cm; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman",serif; mso-fareast-font-family:"Times New Roman";}.MsoChpDefault {mso-style-type:export-only; mso-default-props:yes; font-size:11.0pt; mso-ansi-font-size:11.0pt; mso-bidi-font-size:11.0pt; mso-fareast-language:ES-CO;}.MsoPapDefault {mso-style-type:export-only; mso-pagination:none;}div.WordSection1 {page:WordSection1;}