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2,828 results on '"Altini"'

1. Effectiveness of the flash glucose monitoring system in preventing severe hypoglycemic episodes and in improving glucose metrics and quality of life in subjects with type 1 diabetes at high risk of acute diabetes complications

Author

Dei Cas, Alessandra, Aldigeri, Raffaella, Bellei, Giulia, Raffaeli, Davide, Di Bartolo, Paolo, Sforza, Alessandra, Marchesini, Giulio, Ciardullo, Anna Vittoria, Manicardi, Valeria, Bianco, Maurizio, Monesi, Marcello, Vacirca, Anna, Cimicchi, Maria Cristina, Sordillo, Paola Anna, Altini, Mattia, Fantuzzi, Federica, and Bonadonna, Riccardo C

Published
2024
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5. Enabling Technologies for Optimized Diagnosis, Therapy and Rehabilitation: Obtained Results and Future Works

Author

Brunetti, Antonio, Buongiorno, Domenico, Altini, Nicola, Bevilacqua, Vitoantonio, Lovell, Nigel H., Advisory Editor, Oneto, Luca, Advisory Editor, Piotto, Stefano, Advisory Editor, Rossi, Federico, Advisory Editor, Samsonovich, Alexei V., Advisory Editor, Babiloni, Fabio, Advisory Editor, Liwo, Adam, Advisory Editor, Magjarevic, Ratko, Advisory Editor, Bochicchio, Mario, editor, Siciliano, Pietro, editor, Monteriù, Andrea, editor, Bettelli, Alice, editor, and De Fano, Domenico, editor

Published
2024
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7. Cardiovascular risk evaluation and prevalence of silent myocardial ischemia in subjects with asymptomatic carotid artery disease

Author

Ciccone M, Niccoli AA, Scicchitano P, Gesualdo M, Notaristefano A, Chieppa D, Carbonara S, Ricci G, Sassara, Altini C, Quistelli Giovanni, Lepera ME, Favale S, and Rubini G

Subjects
asymptomatic carotid artery disease, silent myocardial ischemia, myocardial stress scintigraphy., Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Marco Matteo Ciccone1, Artor Niccoli-Asabella2, Pietro Scicchitano1, Michele Gesualdo1, Antonio Notaristefano2, Domenico Chieppa1, Santa Carbonara1, Gabriella Ricci1, Marco Sassara1, Corinna Altini2, Giovanni Quistelli1, Mario Erminio Lepera1, Stefano Favale1, Giuseppe Rubini21Cardiovascular Diseases Section, Department of Emergency and Organ Transplantation (DETO), 2Nuclear Medicine Unit, Department of Internal Medicine and of Public Medicine, University of Bari, Bari, ItalyIntroduction: Silent ischemia is an asymptomatic form of myocardial ischemia, not associated with angina or anginal equivalent symptoms, which can be demonstrated by changes in ECG, left ventricular function, myocardial perfusion, and metabolism. The aim of this study was to evaluate the prevalence of silent myocardial ischemia in a group of patients with asymptomatic carotid stenosis.Methods: A total of 37 patients with asymptomatic carotid plaques, without chest pain or dyspnea, was investigated. These patients were studied for age, sex, hypertension, diabetes, dyslipidemia, smoking, and family history of cardiac disease, and underwent technetium-99 m sestamibi myocardial stress-rest scintigraphy and echo-color Doppler examination of carotid arteries.Results: A statistically significant relationship (P = 0.023) was shown between positive responders and negative responders to scintigraphy test when both were tested for degree of stenosis. This relationship is surprising in view of the small number of patients in our sample. Individuals who had a positive scintigraphy test had a mean stenosis degree of 35% ± 7% compared with a mean of 44% ± 13% for those with a negative test. Specificity of our detection was 81%, with positive and negative predictive values of 60% and 63%, respectively.Conclusion: The present study confirms that carotid atherosclerosis is associated with coronary atherosclerosis and highlights the importance of screening for ischemic heart disease in patients with asymptomatic carotid plaques, considering eventually plaque morphology (symmetry, composition, eccentricity or concentricity of the plaque, etc) for patient stratification.Keywords: asymptomatic carotid artery disease, silent myocardial ischemia, myocardial stress scintigraphy

Published
2011

8. Radiometric Infrared Thermography of Solar Photovoltaic Systems: An Explainable Predictive Maintenance Approach for Remote Aerial Diagnostic Monitoring

Author

Usamah Rashid Qureshi, Aiman Rashid, Nicola Altini, Vitoantonio Bevilacqua, and Massimo La Scala

Subjects
radiometric infrared thermography, solar photovoltaic panel, explainable artificial intelligence, predictive maintenance, intelligent fault detection and diagnosis, Engineering (General). Civil engineering (General), TA1-2040
Abstract

Solar photovoltaic (SPV) arrays are crucial components of clean and sustainable energy infrastructure. However, SPV panels are susceptible to thermal degradation defects that can impact their performance, thereby necessitating timely and accurate fault detection to maintain optimal energy generation. The considered case study focuses on an intelligent fault detection and diagnosis (IFDD) system for the analysis of radiometric infrared thermography (IRT) of SPV arrays in a predictive maintenance setting, enabling remote inspection and diagnostic monitoring of the SPV power plant sites. The proposed IFDD system employs a custom-developed deep learning approach which relies on convolutional neural networks for effective multiclass classification of defect types. The diagnosis of SPV panels is a challenging task for issues such as IRT data scarcity, defect-patterns’ complexity, and low thermal image acquisition quality due to noise and calibration issues. Hence, this research carefully prepares a customized high-quality but severely imbalanced six-class thermographic radiometric dataset of SPV panels. With respect to previous approaches, numerical temperature values in floating-point are used to train and validate the predictive models. The trained models display high accuracy for efficient thermal anomaly diagnosis. Finally, to create a trust in the IFDD system, the process underlying the classification model is investigated with perceptive explainability, for portraying the most discriminant image features, and mathematical-structure-based interpretability, to achieve multiclass feature clustering.

Published
2024
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10. Fit of biokinetic data in molecular radiotherapy: a machine learning approach

Author

Davide Ciucci, Bartolomeo Cassano, Salvatore Donatiello, Federica Martire, Antonio Napolitano, Claudia Polito, Elena Solfaroli Camillocci, Gianluca Cervino, Ludovica Pungitore, Claudio Altini, Maria Felicia Villani, Milena Pizzoferro, Maria Carmen Garganese, and Vittorio Cannatà

Subjects
Machine learning, Akaike information criterion, F-test, Fit function, Biokinetic curves, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Background In literature are reported different analytical methods (AM) to choose the proper fit model and to fit data of the time-activity curve (TAC). On the other hand, Machine Learning algorithms (ML) are increasingly used for both classification and regression tasks. The aim of this work was to investigate the possibility of employing ML both to classify the most appropriate fit model and to predict the area under the curve (τ). Methods Two different ML systems have been developed for classifying the fit model and to predict the biokinetic parameters. The two systems were trained and tested with synthetic TACs simulating a whole-body Fraction Injected Activity for patients affected by metastatic Differentiated Thyroid Carcinoma, administered with [131I]I-NaI. Test performances, defined as classification accuracy (CA) and percentage difference between the actual and the estimated area under the curve (Δτ), were compared with those obtained using AM varying the number of points (N) of the TACs. A comparison between AM and ML were performed using data of 20 real patients. Results As N varies, CA remains constant for ML (about 98%), while it improves for F-test (from 62 to 92%) and AICc (from 50 to 92%), as N increases. With AM, $$\Delta \tau$$ Δ τ can reach down to − 67%, while using ML $$\Delta \tau$$ Δ τ ranges within ± 25%. Using real TACs, there is a good agreement between τ obtained with ML system and AM. Conclusions The employing of ML systems may be feasible, having both a better classification and a better estimation of biokinetic parameters.

Published
2024
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16. Performance and limitations of a supervised deep learning approach for the histopathological Oxford Classification of glomeruli with IgA nephropathy

Author

Altini, Nicola, Rossini, Michele, Turkevi-Nagy, Sándor, Pesce, Francesco, Pontrelli, Paola, Prencipe, Berardino, Berloco, Francesco, Seshan, Surya, Gibier, Jean-Baptiste, Pedraza Dorado, Aníbal, Bueno, Gloria, Peruzzi, Licia, Rossi, Mattia, Eccher, Albino, Li, Feifei, Koumpis, Adamantios, Beyan, Oya, Barratt, Jonathan, Vo, Huy Quoc, Mohan, Chandra, Nguyen, Hien Van, Cicalese, Pietro Antonio, Ernst, Angela, Gesualdo, Loreto, Bevilacqua, Vitoantonio, and Becker, Jan Ulrich

Published
2023
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19. Algor-ethics: charting the ethical path for AI in critical care

Author

Montomoli, J, Bitondo, M, Cascella, M, Rezoagli, E, Romeo, L, Bellini, V, Semeraro, F, Gamberini, E, Frontoni, E, Agnoletti, V, Altini, M, Benanti, P, Bignami, E, Montomoli J., Bitondo M. M., Cascella M., Rezoagli E., Romeo L., Bellini V., Semeraro F., Gamberini E., Frontoni E., Agnoletti V., Altini M., Benanti P., Bignami E. G., Montomoli, J, Bitondo, M, Cascella, M, Rezoagli, E, Romeo, L, Bellini, V, Semeraro, F, Gamberini, E, Frontoni, E, Agnoletti, V, Altini, M, Benanti, P, Bignami, E, Montomoli J., Bitondo M. M., Cascella M., Rezoagli E., Romeo L., Bellini V., Semeraro F., Gamberini E., Frontoni E., Agnoletti V., Altini M., Benanti P., and Bignami E. G.

Abstract

The integration of Clinical Decision Support Systems (CDSS) based on artificial intelligence (AI) in healthcare is groundbreaking evolution with enormous potential, but its development and ethical implementation, presents unique challenges, particularly in critical care, where physicians often deal with life-threating conditions requiring rapid actions and patients unable to participate in the decisional process. Moreover, development of AI-based CDSS is complex and should address different sources of bias, including data acquisition, health disparities, domain shifts during clinical use, and cognitive biases in decision-making. In this scenario algor-ethics is mandatory and emphasizes the integration of ‘Human-in-the-Loop’ and ‘Algorithmic Stewardship’ principles, and the benefits of advanced data engineering. The establishment of Clinical AI Departments (CAID) is necessary to lead AI innovation in healthcare, ensuring ethical integrity and human-centered development in this rapidly evolving field.

Published
2024

22. Fichte

Author

Carlo Altini, AA.VV.

Published
2023

25. 3-T magnetic resonance–guided high-intensity focused ultrasound (3 T-MR-HIFU) for the treatment of pain from bone metastases of solid tumors

Author

Bongiovanni, Alberto, Foca, Flavia, Oboldi, Devil, Diano, Danila, Bazzocchi, Alberto, Fabbri, Laura, Mercatali, Laura, Vanni, Silvia, Maltoni, Marco, Bianchini, David, Casadei, Carla, Matteucci, Federica, Nanni, Oriana, Rossi, Benedetta, Sintuzzi, Emanuele, Martoni, Maria Elena, Zavoiu, Venetia, Barone, Domenico, Altini, Mattia, and Ibrahim, Toni

Published
2022
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27. A Decision-tree Approach to Stratify DLBCL Risk Based on Stromal and Immune Microenvironment Determinants

Author

Gian Maria Zaccaria, Maria Carmela Vegliante, Giuseppe Mezzolla, Marianna Stranieri, Giacomo Volpe, Nicola Altini, Grazia Gargano, Susanna Anita Pappagallo, Antonella Bucci, Flavia Esposito, Giuseppina Opinto, Felice Clemente, Antonio Negri, Paolo Mondelli, Maria Stella De Candia, Vitoantonio Bevilacqua, Attilio Guarini, and Sabino Ciavarella

Subjects
Diseases of the blood and blood-forming organs, RC633-647.5
Published
2023
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28. Radiotherapy and palliative care outpatient clinic: a new healthcare integrated model in Italy

Author

Rossi, Romina, Foca, Flavia, Tontini, Luca, Pieri, Martina, Micheletti, Simona, Nanni, Oriana, Altini, Mattia, Massa, Ilaria, Pallotti, Maria Caterina, Ricci, Marianna, Romeo, Antonino, Muolo, Maria Giustina, Galeotti, Gianluca, Valenti, Vanessa, Tenti, Maria Valentina, Donati, Costanza Maria, Pensieri, Maria Vittoria, Morganti, Alessio Giuseppe, and Maltoni, Marco

Published
2023
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30. Segmentation of diagnostic tissue compartments on whole slide images with renal thrombotic microangiopathies (TMAs).

Author

Huy Q. Vo, Pietro Antonio Cicalese, Surya Seshan, Syed Asad Rizvi, Aneesh Vathul, Gloria Bueno, Aníbal Pedraza Dorado, Niels Grabe, Katharina Stolle, Francesco Pesce, Joris J. T. H. Roelofs, Jesper Kers, Vitoantonio Bevilacqua, Nicola Altini, Bernd Schröppel, Dario Roccatello, Antonella Barreca, Savino Sciascia, Chandra Mohan, Hien Van Nguyen, and Jan U. Becker

Published
2023
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34. Multi-class Tissue Classification in Colorectal Cancer with Handcrafted and Deep Features

Author

Altini, Nicola, Marvulli, Tommaso Maria, Caputo, Mariapia, Mattioli, Eliseo, Prencipe, Berardino, Cascarano, Giacomo Donato, Brunetti, Antonio, Tommasi, Stefania, Bevilacqua, Vitoantonio, De Summa, Simona, Zito, Francesco Alfredo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Huang, De-Shuang, editor, Jo, Kang-Hyun, editor, Li, Jianqiang, editor, Gribova, Valeriya, editor, and Bevilacqua, Vitoantonio, editor

Published
2021
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35. Prognostic factors in children and adolescents with differentiated thyroid carcinoma treated with total thyroidectomy and RAI: a real-life multicentric study

Author

Cistaro, Angelina, Quartuccio, Natale, Garganese, Maria Carmen, Villani, Maria Felicia, Altini, Claudio, Pizzoferro, Milena, Piccardo, Arnoldo, Cabria, Manlio, Massollo, Michela, Maghnie, Mohamad, Campennì, Alfredo, Siracusa, Massimiliano, Baldari, Sergio, Panareo, Stefano, Urso, Luca, Bartolomei, Mirco, De Palma, Diego, Grossi, Armando, Mazzoletti, Angelica, Dondi, Francesco, Bertagna, Francesco, Giubbini, Raffaele, and Albano, Domenico

Published
2022
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37. Human Papillomavirus Genotypes in Invasive Cervical Carcinoma in HIV-Seropositive and HIV-Seronegative Women in Zimbabwe

Author

Mudini, Washington, Palefsky, Joel M, Hale, Martin J, Chirenje, Michael Z, Makunike-Mutasa, Rudo, Mutisi, Fiona, Murahwa, Alltalents, and Mario, Altini

Subjects
Cervical Cancer, Sexually Transmitted Infections, Cancer, Clinical Research, Genetics, Vaccine Related, HPV and/or Cervical Cancer Vaccines, Immunization, Infectious Diseases, Clinical Trials and Supportive Activities, Prevention, HIV/AIDS, Infection, Adult, Alphapapillomavirus, Cross-Sectional Studies, Female, Genotype, HIV Seronegativity, HIV Seropositivity, Humans, Middle Aged, Neoplasm Invasiveness, Tumor Virus Infections, Uterine Cervical Neoplasms, Zimbabwe, cervical cancer, HPV, HIV, dot-blot hybridization, Clinical Sciences, Public Health and Health Services, Virology
Abstract

BackgroundInvasive cervical carcinoma (ICC) accounts for 23% of all cancer-related deaths in Zimbabwean women. Trials for a national program of genotype-specific human papillomavirus (HPV) vaccines are underway to prevent cervical carcinoma, but the distribution of HPV types among women with ICC according to HIV status is unknown.MethodsTo determine prevalence and distribution of high-risk HPV genotypes by HIV status in women with ICC, we performed a cross-sectional study on women referred for ICC testing at 4 urban referral hospitals in Zimbabwe from June 2014 to December 2015. Cervical biopsies were obtained for histology and HPV genotyping. HIV serology testing was performed. HPV testing was performed using MY09/MY11 polymerase chain reaction followed by typing using dot-blot hybridization.ResultsOf 107 participants with histologically proven ICC, HIV prevalence was 49.5% (53/107). HIV-positive women tended to be younger (median age 44 years) than HIV-negative women (median age 59 years). HPV prevalence was 94% (101/107), ranging from 1 to 5 genotypes per participant. HPV 16 (81.5%), 18 (24%), 33 (13%), 35 (11%), 56 (9%), and 45 (7.4%) were the most prevalent genotypes among HIV-negative participants; HPV 16 (67.9%), 18 (43.4%), 56 (18.9%), 45 (15.1%), 33 (11.3%), and 58 (9.4%) were the most prevalent among HIV-positive participants. Eighty-three percent of women were infected with either HPV-16 or HPV-18.ConclusionsEffective vaccination programs against HPV 16 and HPV 18 could prevent up to 83% of cases of cervical cancer in Zimbabwe. HIV may influence distribution of some HPV genotypes given the significant increase in prevalence of HPV 18 among HIV-positive participants.

Published
2018

43. A Tversky Loss-Based Convolutional Neural Network for Liver Vessels Segmentation

Author

Altini, Nicola, Prencipe, Berardino, Brunetti, Antonio, Brunetti, Gioacchino, Triggiani, Vito, Carnimeo, Leonarda, Marino, Francescomaria, Guerriero, Andrea, Villani, Laura, Scardapane, Arnaldo, Cascarano, Giacomo Donato, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Huang, De-Shuang, editor, Bevilacqua, Vitoantonio, editor, and Hussain, Abir, editor

Published
2020
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44. A Novel Approach Based on Region Growing Algorithm for Liver and Spleen Segmentation from CT Scans

Author

Prencipe, Berardino, Altini, Nicola, Cascarano, Giacomo Donato, Guerriero, Andrea, Brunetti, Antonio, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Huang, De-Shuang, editor, Bevilacqua, Vitoantonio, editor, and Hussain, Abir, editor

Published
2020
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48. State of the art of 18F-FDG PET/CT application in inflammation and infection: a guide for image acquisition and interpretation

Author

Casali, Massimiliano, Lauri, Chiara, Altini, Corinna, Bertagna, Francesco, Cassarino, Gianluca, Cistaro, Angelina, Erba, Anna Paola, Ferrari, Cristina, Mainolfi, Ciro Gabriele, Palucci, Andrea, Prandini, Napoleone, Baldari, Sergio, Bartoli, Francesco, Bartolomei, Mirco, D’Antonio, Adriana, Dondi, Francesco, Gandolfo, Patrizia, Giordano, Alessia, Laudicella, Riccardo, Massollo, Michela, Nieri, Alberto, Piccardo, Arnoldo, Vendramin, Laura, Muratore, Francesco, Lavelli, Valentina, Albano, Domenico, Burroni, Luca, Cuocolo, Alberto, Evangelista, Laura, Lazzeri, Elena, Quartuccio, Natale, Rossi, Brunella, Rubini, Giuseppe, Sollini, Martina, Versari, Annibale, and Signore, Alberto

Published
2021
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49. The gastroprotective effect of red propolis extract from Northeastern Brazil and the role of its isolated compounds

Author

Boeing, Thaise, Mejía, Jennyfer Andrea Aldana, Ccana-Ccapatinta, Gari Vidal, Mariott, Marihá, Melo Vilhena de Andrade Fonseca Da Silva, Rita de Cássia, de Souza, Priscila, Mariano, Luisa Nathália Bolda, Oliveira, Graziela Regina, da Rocha, Isabelle Moraes, da Costa, Gabriela Altini, de Andrade, Sérgio Faloni, da Silva, Luísa Mota, and Bastos, Jairo Kenupp

Published
2021
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50. Editorial: Measure do not guess: a call to action to end assumed and estimated menstrual cycle phases in research

Author

Burden, Richard J, Altini, Marco, Ferrer, Eva, Flood, Tessa R, Lewin, Gary, Nimphius, Sophia, Phillips, Stuart M, Elliott-Sale, Kirsty J, Burden, Richard J, Altini, Marco, Ferrer, Eva, Flood, Tessa R, Lewin, Gary, Nimphius, Sophia, Phillips, Stuart M, and Elliott-Sale, Kirsty J

Abstract

Several studies have been published in the last year using assumed or estimated menstrual cycle phases. These phases are ‘generated’ solely on regular menstruation. As more of these studies are published, founded on data that was not actually measured, it becomes imperative to grasp the difference between what is measured versus what is assumed or estimated. We need to measure, not guess, to draw valid and meaningful conclusions in a research topic that is riddled with considerable debate over contradicting outcomes. Hence, this editorial is a call to action directed at editors and reviewers. It is intended to raise the quality, practical implications, application and integrity of future studies investigating the effect of menstrual cycle phases on a given outcome. We do not intend to focus on individual papers but want to ensure that female populations can use their reproductive data accurately and effectively.

Published
2024

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