Digital Health
Thesis | RAN-IO: Radiomics as biomArker imaging for NSCLC patients treated with ImmunOtherapy |
Supervisor | Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it) |
Co-Supervisors | Dr. Arsela Prelaj (arsela.prelaj@polimi.it) Aldo Marzullo (aldo.marzullo@polimi.it) |
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Description | Aim: Predicting Immunotherapy (IO) efficacy in Non-Small Cell Lung Cancer (NSCLC) is a crucial unmet clinical need. Beyond Programmed Death Ligand-1 (PD-L1) no other biomarkers are approved. However, PD-L1 is quite Imperfect. Radiomics was recently used as imaging biomarker in NSCLC patients treated with IO. This thesis aim is to find a predictive radiomic signature for NSCLC patients treated with IO Project phases:
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Thesis | CURE-T790M: NSCLC EGFR MUTATED patients pREdicting T790M+ USING AI |
Supervisor | Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it) |
Co-Supervisors | Dr. Arsela Prelaj (arsela.prelaj@polimi.it) |
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Description | Aim: Osimertinib (OSI), a third-generation tyrosine kinase inhibitor (TKI) is now become the standard of care and is given as first line therapy in NSCLC patients with EGFR mutation (mut) since it demonstrated superiority compare to 1st and 2nd generation (G) TKI. Previously, OSI was received in 2nd line after disease progression upon 1st or 2nd generation TKI in around 50% of patients who acquired an exon20 resistance mutation called T790M. Recent data demonstrated that combination therapy with 1st G TKI in first Line obtained the same PFS compare to OSI. Thus predicting the onset of T790M can prolong survival of around 12 months in around 50% using combo therapy in first line and OSI in second line as sequence therapy. The aim of this study is to predict T790M using AI techniques by integrating all data of NSCLC patients with EGFR mut (Fig in the right). Project phases:
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Thesis | Multimodaldata integration using explainable AI to predict the efficacy of immunotherapy in lung cancer patients |
Supervisor | Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it) |
Co-Supervisors | PhD Vanja Miskovic (vanja.miskovic@polimi.it)
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Collaborations | Istituto Nazionale dei Tumori Milano (INT), Arsela Prelaj MD |
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Description | Aim: Lung cancer is the leading cause of cancer-related death globally. In the last years Immunotherapy (IO), changed the therapeutic and prognostic process. The big challenge is to select the patients that would benefit from the IO treatment. Machine and Deep Learning (ML and DL) methodologies are able to analyze complex behaviors, from different types of data and increase the accuracy of prediction biomarkers leading to the selection of patients who can benefit from IO. In this project, we aim to develop an explainable AI model that uses multi-omics and real-world data to predict the efficacy of IO in Non-small-cell-lung-cancer patients (NSCLC). Project phases:
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Thesis | Prendiciting Immuno-therapy response using AI in NSCLC patients integrating multiomics data |
Supervisor | Prof. Alessandra Pedrocchi (alessandra.pedrocchi@polimi.it) |
Co-Supervisors | Dr. Arsela Prelaj (arsela.prelaj@polimi.it) |
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Description | Aim: Predicting Immunotherapy (IO) efficacy oin NSCLC is a crucial unmet clinical need. Beyond Programmed Death Ligand-1 (PD-L1) no other biomarkers are approved. However, PD-L1 is quite Imperfect. Thus, AI which is able to integrate high dimensional real world and multiomics data could be a unique approach able To find an algorithm able to predict IO in NSCLC patients. The later will be this thesis aim. Project phases:
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Thesis | Development of an application to promote upper limb exosuit user engagement and monitor motor performance |
Supervisor | Prof Simona Ferrante (simona.ferrante@polimi.it) Prof. Emilia Ambrosini |
Co-Supervisors | Chiara Piazzalunga |
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Thesis | Development of a multiplayer videogame to promote the inclusion of disabled children |
Supervisor | Prof Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Chiara Piazzalunga(chiara.piazzalunga@polimi.it) |
Collaborations | ActivE3 project (Politecnico di Milano, Lecco Campus), TecnoBody (Dalmine, BG) |
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Thesis | Serious games for Specific Learning Disorders prevention and training |
Supervisor | Prof Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Chiara Piazzalunga(chiara.piazzalunga@polimi.it) |
Collaborations | Essence project, Indipote(dn)s project, Prof. Cristiano Termine (Università dell’Insubria, Fondazione Macchi) |
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Thesis | Speech emotion recognition and longitudinal monitoring of cognitive decline through mobile app |
Supervisor | Prof Simona Ferrante (simona.ferrante@polimi.it) Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it) |
Co-Supervisors | Chiara Giangregorio (chiara.giangregorio@polimi.it) |
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Thesis | Detection and analysis of cough in lung cancer patients |
Supervisor | Prof Simona Ferrante (simona.ferrante@polimi.it) Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it) |
Co-Supervisors | Chiara Giangregorio (chiara.giangregorio@polimi.it) |
Collaborations | Istituto Nazionale dei Tumori Milano (INT), Arsela Prelaj MD |
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Description | Aim: It has been proved that 65% of people with lung cancer have a chronic cough by the time they’re diagnosed (up to 80% or higher for those with advanced disease). In the context of I3Lung, a European project which “ensures access to innovative, sustainable and high-quality health care”, an app has been developed for the automatic and ecological monitoring of cough in lung cancer patients. This thesis aims to develop a machine (or deep) learning algorithm to analyze cough to ensure therapy’s effectiveness. Project phases:
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Thesis | Machine Learning for premature babies parenteral nutrition |
Supervisor | Prof Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Linda Greta Dui (lindagreta.dui@polimi.it) |
Collaborations | Marco Frontini (Link Up s.r.l.) Valentina Bozzetti (Ospedale San Gerardo, Monza) |
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Description | Aim: Premature babies need a special nutrition program to overcome their frailty condition. It must balance different nutrients apport, to achieve a target growth. However, the real effect of different nutrition programs is still unclear. The aim of this work is the creation of a machine learning model on babies’ response to nutritional programs and the impact on their global health. Project phases:
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Thesis | Monitoring of patients with Parkinson’s disease during walking in free-living and challenging conditions |
Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Milad Malavolti (milad.malavolti@polimi.it) Monica Parati (monica.parati@polimi.it) |
Collaborations | IRCCS Istituti Clinici Scientifici Maugeri, Milano |
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Description | Aim: Gait impairments, including bradykinesia and freezing of gait (FoG), are the most common and disabling symptoms in Parkinson’s disease patients. Quantifying gait impairments under free-living and challenging condition (e.g. FoG-provoking test) using sensing technologies is a promising avenue to assess and monitor disease severity. The aim of this work is to use sensing technologies to quantify gait impairment in Parkinson’s disease, with the final aim of defining tailored interventions. Project phases:
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Thesis | Handwriting Analysis in Primary School Children with an IoT Smart Ink Pen |
Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Simone Toffoli |
Collaborations | Università degli Studi dell’Insubria |
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Description | Aim: 10 to 30% of pupils in primary school show difficulties in mastering handwriting movement skills, a condition known as dysgraphia. Such difficulties have a negative impact on many aspects, like the child’ self-esteem, personal relationship, academic and employment achievements. The diagnosis is performed during grade 3 and is based on the qualitative observation of the handwritten product. National guidelines suggest the development of quantitative approaches for the analysis of children’s handwriting performance (process analysis) in order to: i) create normative data for Italian children of primary school; ii) compare normally developing pupils and children classified as dysgraphic by current clinical protocols. The thesis aim is the collection of handwriting data from pupils with a smart ink pen developed at Nearlab, followed by data analysis. Project phases:
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Thesis | IoT smart ink pen for early detection and monitoring of patients with mild cognitive impairments and dementia |
Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Francesca Lunardini (francesca.lunardini@polimi.it) Simone Toffoli (simone.toffoli@polimi.it) |
Collaborations | IRCCS Fondazione Don Carlo Gnocchi ONLUS |
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Description | Aim: The aim of this work is to use an IoT smart ink pen for the characterization of patients with dementia and mild cognitive impairment with the final goal of supporting early diagnosis. Project phases:
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Thesis | IoT smart ink pen for early detection and monitoring of patients with Parkinson’s disease |
Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Francesca Lunardini (francesca.lunardini@polimi.it) Monica Parati (monica.parati@polimi.it) |
Collaborations | IRCCS Istituti Clinici Scientifici Maugeri, Milano |
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Description | Aim: The diagnosis of clinically probable Parkinson’s Disease (PD) in the early stages relies primarily on clinical assessment by a neurologist. When motor symptoms affect the dominant hand, patients may report worsening of handwriting as of the initial symptoms. The aim of this work is to use an IoT smart ink pen for the characterization of PD patients handwriting, with the final goal of supporting PD patients’ diagnosis and remote monitoring Project phases:
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Thesis | Companion interface for an IoT smart ink pen |
Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Milad Malavolti (milad.malavolti@polimi.it) |
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Description | Aim: Handwriting is a high-value task entailing a unique blend of cognitive, perceptual, and fine motor skills and for this reason its assessment is leveraged in a number of health-related applications, One of the aim of the European ESSENCE project is to leverage a novel IoT smart in pen to monitor user’s handwriting. The aim of this thesis work is to develop a companion interface to manage – via Bluetooth – communication, data recording, data download and important functionalities related to the pen use. Project phases:
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Thesis | The DYSPA System: a novel neuro-motor assessment to quantify dystonia and spasticity in children with movement disorders |
Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisors | Francesca Lunardini (francesca.lunardini@polimi.it) |
Collaborations | Dott. Giovanna Zorzi, Dott. Davide Rossi, Fondazione IRRCS Istituto Neurologico Carlo Besta |
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Description | Aim: Selecting and evaluating appropriate treatment for children with hypertonic movement disorders is nontrivial. One challenge is the ability of quantifying the presence and importance of motor impairments, especially when more than one coexist. This is the case, for instance, of mixed hypertonia with components of spasticity and dystonia. Against this background, the DYSPA System aims at achieving quantitative assessment, encompassing kinematic and electromyographic measures, that quantifies neuro-motor performance during functional tasks and measures the presence and extent of motor impairments through specific dystonia and spasticity indices. Project phases:
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Thesis | Computer Vision and IoT to detect grasping difficulties |
Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) Prof. Matteo Matteucci (matteo.matteucci@polimi.it) |
Co-Supervisors | Linda Greta Dui (lindagreta.dui@polimi.it) |
Collaborations | Università dell’Insubria/Fondazione Macchi (prof Cristiano Termine) Provveditorato di Varese (Luigi Macchi, Simonetta Bralia) |
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Description | Aim: An inefficient grasping position causes difficulties in handwriting and an early correction can avoid persistent problems. In distance learning, teachers’ or experts’ direct observation was not possible. Project phases:
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Thesis | Voice analysis to diagnose neurodegenerative diseases |
Supervisor | Prof. Emilia Ambrosini (emilia.ambrosini@polimi.it) |
Co-Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) |
Collaborations | Dott. Andrea Arighi, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico |
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Description | Aim: Voice signals provide important information to measure human behaviors and cognitive functions. Various types of neurodegenerative dementia (Alzheimer’s disease, frontotemporal dementia, primary progressive aphasia, Lewy body dementia) affect human speech in different manners. Disorders or irregularities in language domain, evaluated in terms of temporal features, such as pauses, speech rate, pitch, etc, could be strong predictors of different neurodegenerative pathologies affecting the brain. This thesis aims at the development and validation of a software tool able to automatically extract a set of language features sensitive and to classify neurodegenerative disorders from voice signals. Project phases: Starting from a Matlab-algorithm to automatically extract voice features from recordings and a dataset of recordings on healthy elderly subjects: – Literature review on vocal indicators of cognitive decline Requirements:
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Thesis | Eye tracking for action observation treatment in neurological patients |
Supervisor | Prof. Simona Ferrante (simona.ferrante@polimi.it) |
Co-Supervisor | Francesca Lunardini (francesca.lunardini@polimi.it) |
Collaborations | Dr. Davide Sebastiano Rossi, Fondazione Istituto Neurologico C. Besta, Milano Prof. Giovanni Buccino, Università Vita-Salute San Raffaele and Division of Neuroscience |
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Description | Aim: Studies show that the use of systematic observation of meaningful actions followed by their execution (action observation treatment [AOT]) may become a rehabilitative strategy to accelerate the process of functional recovery in patients with motor impairment. This work aims at developing a home-based system for neurological patients that leverages eye tracking technology during the observation of video clips showing appropriate actions, with the aim of evaluating compliance to the required task. Project phases: – Literature review |