Projects

Current Projects

UnderXAI

Understanding Ovarian Cancer initiation and progression through Explainable Artificial Intelligence.
We develop an explainable AI-driven decision-support system for assisting the clinicians in making well-informed diagnosis and therapy decisions, ultimately leading to improved treatment outcomes for patients affected by ovarian cancer.

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Francesca Fati

Alice Traversa

CAL.HUB.BRIA

The project “CAL.HUB.RIA” (CALabria HUB for Innovative and Advanced Research), included in the Health Operational Plan, focuses on two main activities: The development of a platform for collecting and harmonizing data on rare diseases; The implementation of machine learning models to support clinical decision-making in patients with advanced-stage brain gliomas (glioblastoma).

Alessandra Marasi

Eriberto Andrea Franchi

TIMECARE

The objective of the TIMECARE project is to develop artificial intelligence (AI) algorithms that can analyse biosignals to predict cardiovascular events and facilitate early recognition. The project will also develop AI algorithms to analyse videos to detect out-of-hospital cardiac arrest (OHCA) and augmented reality (AR) methods to deliver patient-specific cardiopulmonary resuscitation (CPR) and defibrillation. The ultimate goal is to reduce mortality and disability.

Matteo Di Mauro

Junling Fu

Redit

REDIT

Robot-assisted Remote Echography for Diagnosis and Treatment

The REDIT project aims to empower ultrasound specialists to perform remote diagnostic exams, addressing challenges in isolated or mobile settings lacking on-site specialists. The core objectives encompass:
1) the development of a shared-autonomous robotic ultrasound scanning system, with embedded AI-enabled techniques to guide the transducer and avoid missing suspicious regions
2) the refinement of augmented interfaces, i.e., Augmented Reality (AR), to enhance the ergonomics and efficacy of remote ultrasound-guided diagnosis and interventions
3) a rigorous health technology assessment, emphasizing system transparency and usability through extensive validation on phantom models.

Junling Fu

PREDICT

Latest Project

PREDICT

Funded by the Fondazione Regionale per la Ricerca Biomedica — aims to advance ovarian cancer care through the integration of advanced generative and predictive artificial intelligence. By leveraging diagnostic computed tomography (CT) scans and clinical data, the project develops AI models capable of forecasting tumor progression and chemotherapy response. This approach seeks to reduce unnecessary surgeries, optimize treatment planning, and improve both patient outcomes and healthcare efficiency.

Francesca Fati

Alice Traversa

UNCAN

Latest Project

UNCAN

Funded by the EU under Horizon Europe. It builds a federated cancer research data hub following the FAIR principles (Findable, Accessible, Interoperable, Reusable), integrating clinical, biological, and lifestyle information across diverse cancer patients in Europe. The goal is to accelerate prevention, early diagnosis, and treatment research, advancing precision medicine and improving patient outcomes

Laura Cruciani

Alice Traversa

Cariplo

Latest Project

CARIPLO

The project aims to make clinical trials more generalizable and inclusive by using AI and in-silico modeling.
It will create tools to identify subject groups, harmonize data from different institutions, and handle missing information.
Generative models will be used to simulate under-represented populations, helping predict how diverse groups might respond to treatments.
Ultimately, the project seeks to improve trust, diversity, and real-world relevance in evidence-based medicine by automatically assessing how well trial results apply to individual patients and informing future guidelines for more equitable clinical research.

Aldo Marzullo

Eriberto Andrea Franchi

LyNAR

Latest Project

We are developing an augmented reality–based surgical guidance system designed to improve intra-operative localization of metastatic lymph nodes in robotic-assisted radical prostatectomy. By fusing pre-operative PET/CT 3D reconstructions with live endoscopic views, the platform delivers real-time anatomical insights directly into the surgeon’s field of view—helping to reduce missed nodes and enhance oncological results.

Laura Cruciani

Eleonora Pollini

SpectraBreast

Latest Project

SpectraBreast is an EU-funded initiative under the European Innovation Council Pathfinder Open 2024.
The project aims to provide surgeons with a fast, real-time tool to accurately assess tumor margins during breast-conserving surgery, by combining hyperspectral imaging, fiber-optic Raman spectroscopy, and AI algorithms.
The goal is to reduce the rate of re-operations due to incomplete tumor removal, improve patient outcomes, reduce costs, and speed up intraoperative decision making.

Anna Bicchi

OptimAI

Latest Project

OptimAI

The OptimAI project focuses on the development of an AI-based surgical copilot to support surgeons during cardiac interventions. Leveraging machine learning and computer vision algorithms, the system will analyze intraoperative video in real-time to detect critical phases and anticipate potential risks during surgery. Carried out in collaboration with Fondazione Alfieri per il Cuore and IRCCS Ospedale San Raffaele (Milan), the project ultimately aims to enhance patient safety and the efficiency of surgical procedures by reducing the risk of errors and improving patient outcomes.

Rossella Damiano

Past Projects

The Artery project

ARTERY is a radiation-free approach based on shared-autonomy robotic catheters, with increased user engagement and easy interaction.

The fusion of the information yielded by echocardiography, optical and electromagnetic sensing techniques will provide a superior view upon the cardiovascular space.

Fluidic actuation paired with artificial intelligence will be the pillars motors of the next generation of robotic catheters that autonomously find their way towards the target site.

Through a fully immersive augmented reality interface, the operator will monitor the intravascular route of the catheter with no need for radiation-based imaging

Partners

Sant’Anna University (Pisa, IT) – KU Leuven (Leuven, BE) – IRCCS San Raffaele Hospital (Milano, IT) – SwissVortex (Zürich, SW) – Artiness (Milano, IT) – FBGs (Jena, GE)

ATLAS develops smart flexible robots that autonomously propel through complex deformable tubular structures. This calls for seamless integration of sensors, actuators, modelling and control.

By engaging in this ambitious research topic, participants will be exposed to all aspects of robotics. While contributing to the state of the art, they will become proficient in building, modelling, testing, interfacing in short in integrating basic building blocks into systems that display sophisticated behavior.

The Atlas project

Partners

KU Leuven (Leuven, BE) – Sant’Anna School of Advanced Studies (Pisa, IT) – University Of Verona (Verona, IT) – University of Strasbourg (Strasbourg, FR) – Delft University of Technology (Delft, NE) – Polytechnic University of Catalonia (Barcelona, SP)

The Dih-hero project

DIH-HERO’s primary objective is to accelerate innovation in robotics for healthcare.

To connect innovators, providers, businesses, users and politicians, DIH-HERO will establish an open online portal offering multiple services facilitating collaboration on various innovations, emphasizing the sharing of best practice and enhancing the delivery of innovation throughout the value chain.

DIH-HERO especially focuses on supporting small and medium-sized enterprises in maximizing their impact and reducing time-to-market

Find Us

NEARLab is located inside the Leonardo Robotics Labs space at Politecnico di Milano, piazza Leonardo da Vinci 32, Building 7, 20133, Milano, Italy
and at Campus Colombo in Via Giuseppe Colombo, 40, 20133 Milano MI

Hours

Monday to Friday: 8.00 A.M. – 20.00 P.M.

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Benjamin Fortuno, Matteo Di Mauro, Alessandra Maria Trapani

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