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Article ; Online: Discovering Composite Lifestyle Biomarkers With Artificial Intelligence From Clinical Studies to Enable Smart eHealth and Digital Therapeutic Services

Sofoklis Kyriazakos / Aristodemos Pnevmatikakis / Alfredo Cesario / Konstantina Kostopoulou / Luca Boldrini / Vincenzo Valentini / Giovanni Scambia

Frontiers in Digital Health, Vol

2021 Volume 3

Abstract: Discovery of biomarkers is a continuous activity of the research community in the clinical domain that recently shifted its focus toward digital, non-traditional biomarkers that often use physiological, psychological, social, and environmental data to ... ...

Abstract	Discovery of biomarkers is a continuous activity of the research community in the clinical domain that recently shifted its focus toward digital, non-traditional biomarkers that often use physiological, psychological, social, and environmental data to derive an intermediate biomarker. Such biomarkers, by triggering smart services, can be used in a clinical trial framework and eHealth or digital therapeutic services. In this work, we discuss the APACHE trial for determining the quality of life (QoL) of cervical cancer patients and demonstrate how we are discovering a biomarker for this therapeutic area that predicts significant QoL variations. To this extent, we present how real-world data can unfold a big potential for detecting the cervical cancer QoL biomarker and how it can be used for novel treatments. The presented methodology, derived in APACHE, is introduced by Healthentia eClinical solution, and it is beginning to be used in several clinical studies.
Keywords	digital biomarkers ; machine learning ; ai clinical trials ; Healthentia ; real world data ; e-clinical platform ; Medicine ; R ; Public aspects of medicine ; RA1-1270 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	310
Language	English
Publishing date	2021-09-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: FORECAST – A cloud-based personalized intelligent virtual coaching platform for the well-being of cancer patients

Sofoklis Kyriazakos / Vincenzo Valentini / Alfredo Cesario / Robert Zachariae

Clinical and Translational Radiation Oncology, Vol 8, Iss C, Pp 50-

2018 Volume 59

Abstract: Well-being of cancer patients and survivors is a challenge worldwide, considering the often chronic nature of the disease. Today, a large number of initiatives, products and services are available that aim to provide strategies to face the challenge of ... ...

Abstract	Well-being of cancer patients and survivors is a challenge worldwide, considering the often chronic nature of the disease. Today, a large number of initiatives, products and services are available that aim to provide strategies to face the challenge of well-being in cancer patients; nevertheless the proposed solutions are often non-sustainable, costly, unavailable to those in need, and less well-received by patients. These challenges were considered in designing FORECAST, a cloud-based personalized intelligent virtual coaching platform for improving the well-being of cancer patients. Personalized coaching for cancer patients focuses on physical, mental, and emotional concerns, which FORECAST is able to identify. Cancer patients can benefit from coaching that addresses their emotional problems, helps them focus on their goals, and supports them in coping with their disease-related stressors. Personalized coaching in FORECAST offers support, encouragement, motivation, confidence, and hope and is a valuable tool for the wellbeing of a patient.
Keywords	Cancer coaching ; Personalized medicine ; Cloud eHealth platforms ; Medical physics. Medical radiology. Nuclear medicine ; R895-920 ; Neoplasms. Tumors. Oncology. Including cancer and carcinogens ; RC254-282
Subject code	610
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: KIT 1 (Keep in Touch) Project—Televisits for Cancer Patients during Italian Lockdown for COVID-19 Pandemic

Calogero Casà / Barbara Corvari / Francesco Cellini / Patrizia Cornacchione / Andrea D’Aviero / Sara Reina / Silvia Di Franco / Alessandra Salvati / Giuseppe Ferdinando Colloca / Alfredo Cesario / Stefano Patarnello / Mario Balducci / Alessio Giuseppe Morganti / Vincenzo Valentini / Maria Antonietta Gambacorta / Luca Tagliaferri

Healthcare, Vol 11, Iss 1950, p

The Real-World Experience of Establishing a Telemedicine System

2023 Volume 1950

Abstract: To evaluate the adoption of an integrated eHealth platform for televisit/monitoring/consultation during the COVID-19 pandemic. Methods: During the lockdown imposed by the Italian government during the COVID19 pandemic spread, a dedicated multi- ... ...

Abstract	To evaluate the adoption of an integrated eHealth platform for televisit/monitoring/consultation during the COVID-19 pandemic. Methods: During the lockdown imposed by the Italian government during the COVID19 pandemic spread, a dedicated multi-professional working group was set up in the Radiation Oncology Department with the primary aim of reducing patients’ exposure to COVID-19 by adopting de-centralized/remote consultation methodologies. Each patient’s clinical history was screened before the visit to assess if a traditional clinical visit would be recommended or if a remote evaluation was to be preferred. Real world data (RWD) in the form of patient-reported outcomes (PROMs) and patient reported experiences (PREMs) were collected from patients who underwent televisit/teleconsultation through the eHealth platform. Results: During the lockdown period (from 8 March to 4 May 2020) a total of 1956 visits were managed. A total of 983 (50.26%) of these visits were performed via email (to apply for and to upload of documents) and phone call management; 31 visits (1.58%) were performed using the eHealth system. Substantially, all patients found the eHealth platform useful and user-friendly, consistently indicating that this type of service would also be useful after the pandemic. Conclusions: The rapid implementation of an eHealth system was feasible and well-accepted by the patients during the pandemic. However, we believe that further evidence is to be generated to further support large-scale adoption.
Keywords	telemedicine ; digital health ; radiation oncology ; Medicine ; R
Subject code	610
Language	English
Publishing date	2023-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Multidisciplinary Tumor Board Smart Virtual Assistant in Locally Advanced Cervical Cancer

Gabriella Macchia / Gabriella Ferrandina / Stefano Patarnello / Rosa Autorino / Carlotta Masciocchi / Vincenzo Pisapia / Cristina Calvani / Chiara Iacomini / Alfredo Cesario / Luca Boldrini / Benedetta Gui / Vittoria Rufini / Maria Antonietta Gambacorta / Giovanni Scambia / Vincenzo Valentini

Frontiers in Oncology, Vol

A Proof of Concept

2022 Volume 11

Abstract: AimThe first prototype of the “Multidisciplinary Tumor Board Smart Virtual Assistant” is presented, aimed to (i) Automated classification of clinical stage starting from different free-text diagnostic reports; (ii) Resolution of inconsistencies by ... ...

Abstract	AimThe first prototype of the “Multidisciplinary Tumor Board Smart Virtual Assistant” is presented, aimed to (i) Automated classification of clinical stage starting from different free-text diagnostic reports; (ii) Resolution of inconsistencies by identifying controversial cases drawing the clinician’s attention to particular cases worthy for multi-disciplinary discussion; (iii) Support environment for education and knowledge transfer to junior staff; (iv) Integrated data-driven decision making and standardized language and interpretation.Patients and MethodData from patients affected by Locally Advanced Cervical Cancer (LACC), FIGO stage IB2-IVa, treated between 2015 and 2018 were extracted. Magnetic Resonance (MR), Gynecologic examination under general anesthesia (EAU), and Positron Emission Tomography–Computed Tomography (PET-CT) performed at the time of diagnosis were the items from the Electronic Health Records (eHRs) considered for analysis. An automated extraction of eHR that capture the patient’s data before the diagnosis and then, through Natural Language Processing (NLP), analysis and categorization of all data to transform source information into structured data has been performed.ResultsIn the first round, the system has been used to retrieve all the eHR for the 96 patients with LACC. The system has been able to classify all patients belonging to the training set and - through the NLP procedures - the clinical features were analyzed and classified for each patient. A second important result was the setup of a predictive model to evaluate the patient’s staging (accuracy of 94%). Lastly, we created a user-oriented operational tool targeting the MTB who are confronted with the challenge of large volumes of patients to be diagnosed in the most accurate way.ConclusionThis is the first proof of concept concerning the possibility of creating a smart virtual assistant for the MTB. A significant benefit could come from the integration of these automated methods in the collaborative, crucial decision stages.
Keywords	locally advanced cervical cancer ; multidisciplinary tumor board smart virtual assistant ; artificial intelligence ; virtual medicine support ; chemoradiation (CRT) ; Neoplasms. Tumors. Oncology. Including cancer and carcinogens ; RC254-282
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Predictive models in SMA II natural history trajectories using machine learning

Giorgia Coratti / Jacopo Lenkowicz / Stefano Patarnello / Consolato Gullì / Maria Carmela Pera / Carlotta Masciocchi / Riccardo Rinaldi / Valeria Lovato / Antonio Leone / Alfredo Cesario / Eugenio Mercuri

PLoS ONE, Vol 17, Iss 5, p e

A proof of concept study.

2022 Volume 0267930

Abstract: It is known from previous literature that type II Spinal Muscular Atrophy (SMA) patients generally, after the age of 5 years, presents a steep deterioration until puberty followed by a relative stability, as most abilities have been lost. Although it is ... ...

Abstract	It is known from previous literature that type II Spinal Muscular Atrophy (SMA) patients generally, after the age of 5 years, presents a steep deterioration until puberty followed by a relative stability, as most abilities have been lost. Although it is possible to identify points of slope indicating early improvement, steep decline and relative stabilizations, there is still a lot of variability within each age group and it's not always possible to predict individual trajectories of progression from age only. The aim of the study was to develop a predictive model based on machine learning using an XGBoost algorithm for regression and report, explore and quantify, in a single centre longitudinal natural history study, the influence of clinical variables on the 6/12-months Hammersmith Motor Functional Scale Expanded score prediction (HFMSE). This study represents the first approach to artificial intelligence and trained models for the prediction of individualized trajectories of HFMSE disease progression using individual characteristics of the patient. The application of this method to larger cohorts may allow to identify different classes of progression, a crucial information at the time of the new commercially available therapies.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Art and digital technologies to support resilience during the oncological journey

Luca Tagliaferri / Loredana Dinapoli / Calogero Casà / Giuseppe Ferdinando Colloca / Fabio Marazzi / Patrizia Cornacchione / Ciro Mazzarella / Valeria Masiello / Silvia Chiesa / Francesco Beghella Bartoli / Elisa Marconi / Marika D'Oria / Alfredo Cesario / Daniela Pia Rosaria Chieffo / Vincenzo Valentini / Maria Antonietta Gambacorta

Technical Innovations & Patient Support in Radiation Oncology, Vol 24, Iss , Pp 101-

The Art4ART project

2022 Volume 106

Abstract: Introduction: New digital technologies can become a tool for welcoming the patient through the artistic dimension. Cancer patients, in particular, need support that accompanies and supports them throughout their treatment. Materials and methods: The ... ...

Abstract	Introduction: New digital technologies can become a tool for welcoming the patient through the artistic dimension. Cancer patients, in particular, need support that accompanies and supports them throughout their treatment. Materials and methods: The Art4ART project consist in the structural proposal to cancer patients of a web-based digital platform containing several forms of art as video-entertainments; a multimedia immersive room; an art-based welcoming of the patients with several original paintings; an environment with a peacefulness vertical garden; a reconceptualization of the chemotherapy-infusion seats. Data regarding patients’ preference and choices will be stored and analysed also using artificial intelligence (AI) algorithm to measure and predict impact indicators regarding clinical outcomes (survival and toxicity), psychological indicators. Moreover, the same digital platform will contribute to a better organization of the activities. Discussion: Through the systematic acquisition of patient preferences and through integration with other clinical parameters, it will be possible to measure the clinical, psychological, organisational, and social impact of the newly implemented Art4ART project. The use of digital technology leads us to apply the reversal of viewpoint from therapeutic acts to patient-centred care.
Keywords	Digital health ; Cancer ; Radiotherapy ; Resilience ; Patient-centered care ; Medical physics. Medical radiology. Nuclear medicine ; R895-920 ; Neoplasms. Tumors. Oncology. Including cancer and carcinogens ; RC254-282
Language	English
Publishing date	2022-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Personalized Approach for Obese Patients Undergoing Endoscopic Sleeve Gastroplasty

Maria Valeria Matteo / Marika D’Oria / Vincenzo Bove / Giorgio Carlino / Valerio Pontecorvi / Marco Raffaelli / Daniela Chieffo / Alfredo Cesario / Giovanni Scambia / Guido Costamagna / Ivo Boškoski

Journal of Personalized Medicine, Vol 11, Iss 1298, p

2021 Volume 1298

Abstract: Obesity is a chronic, relapsing disease representing a major global health problem in the 21st century. Several etiologic factors are involved in its pathogenesis, including a Western hypercaloric diet, sedentariness, metabolic imbalances, genetics, and ... ...

Abstract	Obesity is a chronic, relapsing disease representing a major global health problem in the 21st century. Several etiologic factors are involved in its pathogenesis, including a Western hypercaloric diet, sedentariness, metabolic imbalances, genetics, and gut microbiota modification. Lifestyle modifications and drugs often fail to obtain an adequate and sustained weight loss. To date, bariatric surgery (BS) is the most effective treatment, but only about 1% of eligible patients undergo BS, partly because of its negligible morbidity and mortality. Endoscopic sleeve gastroplasty (ESG) is a minimally invasive, endoscopic, bariatric procedure, which proved to be safe and effective. In this review, we aim to examine evidence supporting the role of a personalized and multidisciplinary approach, guided by a multidisciplinary team (MDT), for obese patients undergoing ESG, from patient selection to long-term follow-up. The cooperation of different health professionals, including an endocrinologist and/or obesity medicine physician, a bariatric surgeon, an endoscopist experienced in bariatrics, a registered dietitian, an exercise specialist, a behaviour coach, a psychologist, and a nurse or physician extender, aims to induce radical and sustained lifestyle changes. We also discussed the relationship between gut microbiota and outcomes after bariatric procedures, speculating that the characterization of gut microbiota before and after ESG may help develop new tools, including probiotics, to optimize weight loss outcomes.
Keywords	obesity ; bariatric endoscopy ; endoscopic sleeve gastroplasty ; personalized treatment ; multidisciplinary team ; Medicine ; R
Subject code	616
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Building a Personalized Medicine Infrastructure for Gynecological Oncology Patients in a High-Volume Hospital

Nicolò Bizzarri / Camilla Nero / Francesca Sillano / Francesca Ciccarone / Marika D’Oria / Alfredo Cesario / Simona Maria Fragomeni / Antonia Carla Testa / Francesco Fanfani / Gabriella Ferrandina / Domenica Lorusso / Anna Fagotti / Giovanni Scambia

Journal of Personalized Medicine, Vol 12, Iss 3, p

2021 Volume 3

Abstract: Gynecological cancers require complex intervention since patients have specific needs to be addressed. Centralization to high-volume centers improves the oncological outcomes of patients with gynecological cancers. Research in gynecological oncology is ... ...

Abstract	Gynecological cancers require complex intervention since patients have specific needs to be addressed. Centralization to high-volume centers improves the oncological outcomes of patients with gynecological cancers. Research in gynecological oncology is increasing thanks to modern technologies, from the comprehensive molecular characterization of tumors and individual pathophenotypes. Ongoing studies are focusing on personalizing therapies by integrating information across genomics, proteomics, and metabolomics with the genetic makeup and immune system of the patient. Hence, several challenges must be faced to provide holistic benefit to the patient. Personalized approaches should also recognize the unmet needs of each patient to successfully deliver the promise of personalized care, in a multidisciplinary effort. This may provide the greatest opportunity to improve patients’ outcomes. Starting from a narrative review on gynecological oncology patients’ needs, this article focuses on the experience of building a research and care infrastructure for personalized patient management.
Keywords	gynecologic oncology ; patient-centered care ; personalized medicine ; Medicine ; R
Subject code	616
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Role of Artificial Intelligence in Managing Multimorbidity and Cancer

Alfredo Cesario / Marika D’Oria / Riccardo Calvani / Anna Picca / Antonella Pietragalla / Domenica Lorusso / Gennaro Daniele / Franziska Michaela Lohmeyer / Luca Boldrini / Vincenzo Valentini / Roberto Bernabei / Charles Auffray / Giovanni Scambia

Journal of Personalized Medicine, Vol 11, Iss 314, p

2021 Volume 314

Abstract: Traditional healthcare paradigms rely on the disease-centered approach aiming at reducing human nature by discovering specific drivers and biomarkers that cause the advent and progression of diseases. This reductive approach is not always suitable to ... ...

Abstract	Traditional healthcare paradigms rely on the disease-centered approach aiming at reducing human nature by discovering specific drivers and biomarkers that cause the advent and progression of diseases. This reductive approach is not always suitable to understand and manage complex conditions, such as multimorbidity and cancer. Multimorbidity requires considering heterogeneous data to tailor preventing and targeting interventions. Personalized Medicine represents an innovative approach to address the care needs of multimorbid patients considering relevant patient characteristics, such as lifestyle and individual preferences, in opposition to the more traditional “one-size-fits-all” strategy focused on interventions designed at the population level. Integration of omic (e.g., genomics) and non-strictly medical (e.g., lifestyle, the exposome) data is necessary to understand patients’ complexity. Artificial Intelligence can help integrate and manage heterogeneous data through advanced machine learning and bioinformatics algorithms to define the best treatment for each patient with multimorbidity and cancer. The experience of an Italian research hospital, leader in the field of oncology, may help to understand the multifaceted issue of managing multimorbidity and cancer in the framework of Personalized Medicine.
Keywords	personalized medicine ; artificial intelligence ; omics ; geriatrics ; multimorbidity ; gynecological oncology ; Medicine ; R
Language	English
Publishing date	2021-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Translational Research in the Era of Precision Medicine

Ruggero De Maria Marchiano / Gabriele Di Sante / Geny Piro / Carmine Carbone / Giampaolo Tortora / Luca Boldrini / Antonella Pietragalla / Gennaro Daniele / Maria Tredicine / Alfredo Cesario / Vincenzo Valentini / Daniela Gallo / Gabriele Babini / Marika D’Oria / Giovanni Scambia

Journal of Personalized Medicine, Vol 11, Iss 216, p

Where We Are and Where We Will Go

2021 Volume 216

Abstract: The advent of Precision Medicine has globally revolutionized the approach of translational research suggesting a patient-centric vision with therapeutic choices driven by the identification of specific predictive biomarkers of response to avoid ... ...

Abstract	The advent of Precision Medicine has globally revolutionized the approach of translational research suggesting a patient-centric vision with therapeutic choices driven by the identification of specific predictive biomarkers of response to avoid ineffective therapies and reduce adverse effects. The spread of “multi-omics” analysis and the use of sensors, together with the ability to acquire clinical, behavioral, and environmental information on a large scale, will allow the digitization of the state of health or disease of each person, and the creation of a global health management system capable of generating real-time knowledge and new opportunities for prevention and therapy in the individual person (high-definition medicine). Real world data-based translational applications represent a promising alternative to the traditional evidence-based medicine (EBM) approaches that are based on the use of randomized clinical trials to test the selected hypothesis. Multi-modality data integration is necessary for example in precision oncology where an Avatar interface allows several simulations in order to define the best therapeutic scheme for each cancer patient.
Keywords	omics ; personalized medicine ; Precision Medicine ; high-definition medicine ; Medicine ; R
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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