View source for Automatic Idea Detection for controlling Healthcare-associated infections

{{StudentProjectTemplate
|Summary=This project aims to use advanced NLP tools to automatically detect interesting ideas by processing text available in the medical forums to address the Healthcare-associated infections problem in the hospitals
|Keywords=Natural Language Processing (NLP), Automatic Idea Detection (AID),  Healthcare-associated infections (HAI)
|References=[1] Gould, Dinah, et al. "Electronic hand hygiene monitoring: accuracy, impact on the Hawthorne effect and efficiency." Journal of Infection Prevention 21.4 (2020): 136-143.

[2] Christensen, Kasper, et al. "How good are ideas identified by an automatic idea detection system?." Creativity and Innovation Management 27.1 (2018): 23-31.

[3] Chowdhury, Gobinda G. "Natural language processing." Annual review of information science and technology 37.1 (2003): 51-89.
|Prerequisites=Artificial Intelligence, Data Mining; knowledge of natural language processing is a plus
|Supervisor=Fabio Gama, Peyman Mashhadi, Mahmoud Rahat
|Level=Master
|Status=Open
}}
Healthcare-associated infections (HAI) are among the major causes of death of hospitalized patients. Controlling and preventing HAI is difficult because of the complexity of implementing sustainable practices in hospitals, the lack of ways to observe healthcare professional behavior, and companies’ inability to identify HAI prevention practices by themselves.

A proposed way for addressing this is through the use of Automatic Idea Detection (AID) systems. AID system is a classification algorithm based on text processing tools that can screen large amounts of information and identify those likely to contain valuable or novel ideas/treatments. This project intends to explore Professional forums to identify valuable, feasible, and novel ideas and treatments related to HAI. Both cases use English as the main language. The project offers funds for devoted master students to start prototyping the algorithms.

This project has been assigned to a student.