Giuseppe De Pietro

Italian National Research Council | CNR · Institute for High Performance Computing and Networking ICAR

In finance, portfolio optimization aims at finding optimal investments maximizing a trade-off between return and risks, given some constraints. Classical formulations of this quadratic optimization problem have exact or heuristic solutions, but the complexity scales up as the market dimension increases. Recently, researchers are evaluating the poss...

There is a raised interest in literature to use Virtual Reality (VR) technology as an assessment tool for cognitive domains. One of the essential advantages of transforming tests in an immersive virtual environment is the possibility of automatically calculating the test's score, a time-consuming process under natural conditions. Although the chara...

Breast Cancer (BC) is the most common cancer among women worldwide and is characterized by intra- and inter-tumor heterogeneity that strongly contributes towards its poor prognosis. The Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2), and Ki67 antigen are the most examined markers depicting BC het...

Artificial intelligence technologies are considered crucial in supporting a decentralized model of care in which therapeutic interventions are provided from a distance. In the last years, various approaches have been proposed to support remote monitoring and smart assistance in rehabilitation services. A comprehensive state-of-the-art of machine le...

Breast cancer is the most commonly diagnosed cancer and registers the highest number of deaths for women. Advances in diagnostic activities combined with large-scale screening policies have significantly lowered the mortality rates for breast cancer patients. However, the manual inspection of tissue slides by pathologists is cumbersome, time-consum...

In the last decade, the demand for readily accessible corpora has touched all areas of natural language processing, including coreference resolution. However, it is one of the least considered sub-fields in recent developments. Moreover, almost all existing resources are only available for the English language. To overcome this lack, this work prop...

The Urban Intelligence (UI) paradigm conceived by CNR consists of an ecosystem of digital technologies joined within a Digital Twin (DT) of the city aimed at improving the city governance towards goals addressed also by the UN Agenda 2030, such as urban environment, sustainability and resilience, wellbeing and quality of life, local development, an...

The incidence of Head and Neck Squamous Cell Carcinoma (HNSCC) has been growing in the last few decades. Its diagnosis is usually performed through clinical evaluation and analyzing radiological images, then confirmed by histopathological examination, an invasive and time-consuming operation. The recent advances in the artificial intelligence field...

Today, reviews are the advertising medium par excellence through which companies are able to influence customers’ spending decisions. Although the initial purpose of reviews was to provide companies with a feedback tool to improve products and services based on customer needs, they soon became a way to climb the sales rankings, often illegally. In...

Over the years, the attention of the scientific world towards the techniques of sentiment analysis has increased considerably, driven by industry. The arrival of the Google BERT language model has confirmed the superiority of models based on a particular structure of artificial neural network called Transformer, from which many variants have result...

Rehabilitation plays a crucial role in cancer care, as the functioning of cancer survivors is frequently compromised by impairments that can result from the disease itself but also from the long-term sequelae of the treatment. Nevertheless, the current literature shows that only a minority of patients receive physical and/or cognitive rehabilitatio...

Research on fuzzy logic [1] and soft computing for decision making has a long history. In many fields of application, rule-based fuzzy systems have been employed [2–4] for their unique properties in solving modelling problems[...]

The meeting between Natural Language Processing (NLP) and Quantum Computing has been very successful in recent years, leading to the development of several approaches of the so-called Quantum Natural Language Processing (QNLP). This is a hybrid field in which the potential of quantum mechanics is exploited and applied to critical aspects of languag...

Edge Analytics and Artificial Intelligence are important features of the current smart connected living community. In a society where people, homes, cities, and workplaces are simultaneously connected through various devices, primarily through mobile devices, a considerable amount of data is exchanged, and the processing and storage of these data a...

In medical practice, all decisions, as for example the diagnosis based on the classification of images, must be made reliably and effectively. The possibility of having automatic tools helping doctors in performing these important decisions is highly welcome. Artificial Intelligence techniques, and in particular Deep Learning methods, have proven v...

This paper investigates the ability of multilingual BERT (mBERT) language model to transfer syntactic knowledge cross-lingually, verifying if and to which extent syntactic dependency relationships learnt in a language are maintained in other languages. In detail, the main contributions of this paper are: (i) an analysis of the cross-lingual syntact...

Recently, many approaches were proposed to support human resource management in finding the best human resources for available jobs. However, existing solutions do not effectively evaluate employees’ skills, or they do only partially, neither provide mechanisms to describe subjects’ skills and desiderata. To face this issue, this paper proposes a d...

This paper describes a cloud-based platform that offers evidence-based, personalised interventions powered by Artificial Intelligence to help support efficient remote monitoring and clinician-driven guidance to people over 65 who suffer or are at risk of hearing loss, cardiovascular diseases, cognitive impairments, balance disorders, and mental hea...

In last years, coreference resolution has received a sensibly performance boost exploiting different pre-trained Neural Language Models, from BERT to SpanBERT until Longformer. This work is aimed at assessing, for the first time, the impact of ELECTRA model on this task, moved by the experimental evidence of an improved contextual representation an...

Dynamic Treatment Regimes (DTRs) are sets of sequential decision rules that can be adapted over time to treat patients with a specific pathology. DTR consists of alternative treatment paths and any of these treatments can be adapted depending on the patient’s characteristics. Reinforcement Learning (RL) and Imitation Learning (IL) approaches have b...

The ageing of the population creates new heterogeneous challenges for age-friendly living. The progressive decline in physical and cognitive skills tends to prevent elderly people from performing basic instrumental activities of daily living and there is a growing interest in technology for aging support. Digital health today can be exercised by an...

The current wireless communication infrastructure has to face exponential development in mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems and their variants (i.e., Multi-User MIMO and Massive MIMO) are the most promising 5G wireless communication systems technology due to their high system throughput and...

Breast cancer is the most commonly diagnosed cancer and registers the highest number of deaths for women with cancer. Recent advancements in diagnostic activities combined with large-scale screening policies have significantly lowered the mortality rates for breast cancer patients. However, the manual inspection of tissue slides by the pathologists...

In the last years, the rise of digital technologies has enormously augmented the possibility for people to access health information and consult online versions of Patient Information Leaflets (PILs), enabling them to improve their knowledge about medication and adherence to therapies. However, health information may often be difficult to consult a...

Healthcare sensors represent a valid and non-invasive instrument to capture and analyse physiological data. Several vital signals, such as voice signals, can be acquired anytime and anywhere, achieved with the least possible discomfort to the patient thanks to the development of increasingly advanced devices. The integration of sensors with artific...

Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens highly depend on the phenotype and topological distribution of constituting histological entities. Thus, adequate tissue representations for encoding histological entities is imperative for computer aided cancer patient care. To this end, several approaches have lev...

In decision-making problems reward function plays an important role in finding the best policy. Reinforcement Learning (RL) provides a solution for decision-making problems under uncertainty in an Intelligent Environment (IE). However, it is difficult to specify the reward function for RL agents in large and complex problems. To counter these probl...

Although CNNs are widely considered as the state-of-the-art models in various applications of image analysis, one of the main challenges still open is the training of a CNN on high resolution images. Different strategies have been proposed involving either a rescaling of the image or an individual processing of parts of the image. Such strategies c...

The work presented in this paper investigates the ability of BERT neural language model pretrained in Italian to embed syntactic dependency relationships into its layers, by approximating a Dependency Parse Tree. To this end, a structural probe, namely a supervised model able to extract linguistic structures from a language model, has been trained...

The Covid-19 pandemic represents one of the greatest global health emergencies of the last few decades with indelible consequences for all societies throughout the world. The cost in terms of human lives lost is devastating on account of the high contagiousness and mortality rate of the virus. Millions of people have been infected, frequently requi...

Cancer diagnosis and prognosis for a tissue specimen are heavily influenced by the phenotype and topological distribution of the constituting histological entities. Thus, adequate tissue representation by encoding the histological entities, and quantifying the relationship between the tissue representation and tissue functionality is imperative for...

Clinical de-identification aims to identify Protected Health Information in clinical data, enabling data sharing and publication. First automatic de-identification systems were based on rules or on machine learning methods, limited by language changes, lack of context awareness and time consuming feature engineering. Newer deep learning techniques...

Although CNNs are widely considered as the state-of-the-art models in various applications of image analysis, one of the main challenges still open is the training of a CNN on high resolution images. Different strategies have been proposed involving either a rescaling of the image or an individual processing of parts of the image. Such strategies c...

In the last years, the need to de-identify privacy-sensitive information within Electronic Health Records (EHRs) has become increasingly felt and extremely relevant to encourage the sharing and publication of their content in accordance with the restrictions imposed by both national and supranational privacy authorities. In the field of Natural Lan...

In recent years, the impact of Neural Language Models has changed every field of Natural Language Processing. In this scenario, coreference resolution has been among the least considered task, especially in language other than English. This work proposes a coreference resolution system for Italian, based on a neural end-to-end architecture integrat...

the aim of the study was to conduct a meta-analysis to evaluate the efficacy of non-invasive and non-pharmacological techniques on labor first-stage pain intensity. Literature databases were searched from inception to May 2021, and research was expanded through the screening of previous systematic reviews. Inclusion criteria were: (1) population: w...

The COrona VIrus Disease 19 (COVID-19) pandemic required the work of all global experts to tackle it. Despite the abundance of new studies, privacy laws prevent their dissemination for medical investigations: through clinical de-identification, the Protected Health Information (PHI) contained therein can be anonymized so that medical records can be...

Cancer diagnosis, prognosis, and therapeutic response prediction are heavily influenced by the relationship between the histopathological structures and the function of the tissue. Recent approaches acknowledging the structure-function relationship, have linked the structural and spatial patterns of cell organization in tissue via cell-graphs to tu...

Discovering new treatments and personalizing existing ones is one of the major goals of modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the realization of advanced intelligent systems able to learn about clinical treatments and discover new medical knowledge from the huge amount of data collected. Reinforcemen...

Objectives: Investigate and identify the relationship between physical exercise and cognitive performance measured by using different cognitive tests taken from Cambridge Brain Science (CBS). Methods: Thirty subjects, divided into two groups (aerobic and effort), undergo twelve cognitive tests from CBS. A comparison between the pre- and post-exerci...

One of the most important physiological parameters of the cardiovascular circulatory system is Blood Pressure. Several diseases are related to long-term abnormal blood pressure, i.e., hypertension; therefore, the early detection and assessment of this condition are crucial. The identification of hypertension, and, even more the evaluation of its ri...

Question Classification (QC) is of primary importance in question answering systems, since it enables extraction of the correct answer type. State-of-the-art solutions for short text classification obtained remarkable results by Convolutional Neural Networks (CNNs). However, implementing such models requires choices, usually based on subjective exp...

Cancer diagnosis, prognosis, and therapeutic response prediction are heavily influenced by the relationship between the histopathological structures and the function of the tissue. Recent approaches acknowledging the structure-function relationship, have linked the structural and spatial patterns of cell organization in tissue via cell-graphs to tu...

We introduce a machine learning-based analysis to predict the immunohistochemical (IHC) labeling index for the cell proliferation marker Ki67/MIB1 on cancer tissues based on morphometrical features extracted from hematoxylin and eosin (H&E)-stained formalin-fixed, paraffin-embedded (FFPE) tumor tissue samples. We provided a proof-of-concept predict...

Big Data paradigm is leading both research and industry effort calling for new approaches in many computer science areas. In this paper, we show how semantic similarity search for natural language texts can be leveraged in biomedical domain by Word Embedding models obtained by word2vec algorithm, exploiting a specifically developed Big Data archite...

Cutting-edge visualization and interaction technologies are increasingly used in museum exhibitions, providing novel ways to engage visitors and enhance their cultural experience. Existing applications are commonly built upon a single technology, focusing on visualization, motion or verbal interaction (e.g., high-resolution projections, gesture int...

In this paper we propose an architecture specifically devoted to the analysis of huge natural language biomedical textual collections, with the purpose of searching for semantic similarity in order to obtain useful hints for effective simulation that could help physicians in diagnosis tasks. We leverage Word Embedding models trained with word2vec a...

Automatic detection of falls is extremely important, especially in the remote monitoring of elderly people, and will become more and more critical in the future, given the constant increase in the number of older adults. Within this framework, this paper deals with the task of evaluating several artificial intelligence techniques to automatically d...

Performance-based functional tests for the evaluation of daily living activities demonstrate strong psychometric properties and solve many of the limitations associated with self- and informant-report questionnaires. Virtual reality (VR) technology, which has gained interest as an effective medium for administering interventions in the context of h...

Psychological distress is a common consequence of breast cancer diagnosis and treatment and could further exacerbate therapy side effects. Interventions increasing treatment tolerance are crucial to improve both patients' quality of life and adherence to therapies. Virtual reality (VR) has emerged as an effective distraction tool for different medi...

This chapter explores the most relevant aspects in relation to the outcomes and performance of the different components of a healthcare system with a particular focus on mobile healthcare applications. In detail, we discuss the six quality principles to be satisfied by a generic healthcare system and the main international and European projects, wh...

Question Answering (QA) systems based on Information Retrieval return precise answers to natural language questions, extracting relevant sentences from document collections. However, questions and sentences cannot be aligned terminologically, generating errors in the sentence retrieval. In order to augment the effectiveness in retrieving relevant s...

In this paper we address the problem of analyzing biomedical data collection with the purpose of searching for semantic similarity among textual documents. In details, we leverage Word Embeddings models obtained by word2vec algorithm and a specific Big Data architecture for their management, defining an approach able to permit the retrieving of sem...

In the last decade, the quantity of readily accessible text has grown rapidly and enormously, long exceeding the capacity of humans to read and understand it. One of the most interesting strategies proposed to fulfill this need is known as Open Information Extraction (OIE). It is essentially devised to read in sentences and rapidly extract one or m...

Deep Neural Networks (DNNs) may be very effective for the classification over highly-sized data sets, especially in the medical domain, where the recognition of the occurrence of a specific event related to a disease is of high importance. Unfortunately, DNNs suffer from the drawback that a good set of values for their configuration hyper-parameter...

The evolution of the Internet of Things, cloud computing and wireless communication has contributed to an advance in the interconnectivity, efficiency and data accessibility in smart cities, improving environmental sustainability, quality of life and well-being, knowledge and intellectual capital. In this scenario, the satisfaction of security and...

In this paper we present a new 3D descriptor for human classification and a human detection method based on this descriptor. The proposed 3D descriptor allows classification of an object represented by a point cloud, as human or non-human. It is derived from the well-known Histogram of Oriented Gradient by employing surface normals instead of gradi...

Multiple Sclerosis (MS) is a chronic neuroinflammatory disorder of the brain and spinal cord, widely studied nowadays, due to its relevant prevalence in the population. Even though no cure exists, an earlier and more adequate choice of treatment could delay its evolution and prevent irreversible sequelae and disability progression. Currently, Magne...

In the current Italian eHealth scenario, a national IT platform has been designed and developed with the purpose of ensuring the interoperability between the various Electronic Health Record (EHR) systems that have been adopted in the different regions of the country, according to the requirements provided by Italian Laws. In this way, the healthca...

Obstructive sleep apnoea (OSA) is a breathing disorder that takes place in the course of the sleep and is produced by a complete or a partial obstruction of the upper airway that manifests itself as frequent breathing stops and starts during the sleep. The real-time evaluation of whether or not a patient is undergoing OSA episode is a very importan...

Background: Atherosclerosis is a progressive process responsible for most heart diseases and ischemic stroke. It constitutes, in fact, the most common cause of stroke in middle-aged people. To avoid or, at least, limit the disabling deficits that may derive from a carotid disease, a prompt and early diagnosis is necessary. The diagnostic technique...

The rapid diffusion of voice disorders and the lack of appropriate knowledge about the problem have prompted the search for novel and reliable approaches to detect dysphonia, through easy and accessible instruments such as mobile devices. These systems represent, in fact, valid instruments to improve the patient care not only to facilitate the moni...

Accurately identifying and categorizing cancer structures/sub-types in histological images is an important clinical task involving a considerable workload and a specific subspecialty of pathologists. Digitizing pathology is a current trend that provides large amounts of visual data allowing a faster and more precise diagnosis through the developmen...

Questo contributo è rivolto alla descrizione delle attività di ricerche dell’Istituto ICAR-CNR relative all’analisi automatica di immagini digitali mediche svolte all’interno di collaborazioni sceintifiche o progetti finanziati di Ricerca Industriale. Obiettivo di tali collaborazioni è lo sviluppo di nuovi strumenti intelligenti di diagnostica avan...

Una rilevante area di ricerca dell’Istituto di Calco