DIETI Contact person / Partner: Paolo Maresca

Abstract

Health-related analyses generate huge amounts of heterogeneous data. Obtaining knowledge from these “big data” is both challenging and promising for data-driven medicine, that can benefit from AI tools to infer models for such complex problems. The PhD research activities will include model design, optimization, and validation, applied to prospective and retrospective studies, with the support of the MS partner (including data sanitization operations, and resulting analysis and validation). The PhD student will spend at least six months abroad working under the guidance of one or both our foreign partners, University of Warwick (UK) and University of Saint Louis (US).

Objectives

Main goals include the development and application of innovative approaches to prospective and retrospective studies, aimed at modeling the complexity of infectious diseases. The approaches will be supported by AI and Big Data technologies.

DIETI Contact person / Partner: Carlo Sansone

Abstract

Sentinel node (SLN) biopsy is used to stage patients with early-stage breast cancer with clinically negative axillary nodes, but it is invasive and with complications. To overcome such issues this research aims to predict SLNs metastasis using radiomics on T1w-MRI of the native tumor, even in combination with histological features and patients clinical data, supporting treatment decision by providing a non-invasive approach in clinical routine.

Objectives

Development of a radiomic platform to predict sentinel nodes metastasis in a non-invasive ways using artificial intelligence-based methods extracting information from T1w-MR scans and patient clinical data.

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Already assigned to a PhD student of cycle XXXV

DIETI Contact person / Partner: Mario Di Bernardo

Abstract

A key challenge for the development of personalized therapies is the ability of delivering drugs in situ and avoid unwanted side effects to the patients. A promising approach is the use of synthetically engineered cell populations with advanced functionalities whose collective behavior can be carefully controlled so that they can move to the target area and release some drug. This proposal focuses on the development of multicellular control strategies to create microbial consortia in which cell populations cooperate to realize this challenging goal. The project will be supervised by the proponent together with prof Brunetti and prof Surace at the Dept. of Translational Medicine and will involve active collaboration with leading groups at ETH and Bristol and the start-up companies at TIGEM.

Objectives

• Develop synthetic biology approaches for drug delivery based on multicellular consortia;
• Synthesize gene regulatory networks to implement the desired functions in vivo;
• Adopt and develop methods from ICT to achieve multicellular control of bacterial and mammalian cell populations;
• Carry out in-vivo validation using optogenetics and microfluidics platforms.

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DIETI Contact person / Partner: Mario Cesarelli

Abstract

The project consists on the development of an innovative m-Health system based on wearable devices in e-textile technology. M-Health means the provision of healthcare services supported by "mobile" devices which the most recent studies identify as the ICT sector with the greatest future potential expansion; while for e-textile we mean the integration of electronic components directly into washable and sensorized garments, commercially available at low and decreasing costs and suitable for home care based applications.

Objectives

Project, development and experimental setting of e-textile based prototyping t-shirt and socks for biomedical physiological signals and movement analysis' indexes processing.