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Oncological Pain Automatic Assessment

DIETI Contact person / Partner: Nicola Pasquino

Abstract

In oncological patients, pain is one of the most disabling symptoms. The correct approach to pain treatment has a positive impact on her prospectives to afford other therapies for recovery. Therapist defines treatment based on subjective pain scales and continuously refine drug dosages, based on the patient responses, in a loop that sometimes hardly converging. This project aims at creating an automatic pain assessment protocol, based on the collection of multimodal data generated during a patient's life. Patients will be remotely monitored, recording texts (questionnaires), video (self-report), biometric parameters (recorded via personal devices), drug timing scheduling, etcetera. This project falls in the area of big data technologies for health. Physicians will cooperate with computer scientists and data analysts to design, process, and evaluate this flux of data to be used both for real-time monitoring and training of AI systems.

Objective

  • the creation of a dataset for pain assessment substituting subjective scale for self-evaluation;
  • the definition of an interventionist protocol in the field of refining treatments and drug dosages;
  • the design of AI-based decision making systems in the field of big data for oncological purposes.

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Available

Can be assigned to one doctoral student of cycle XXXVI 

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