Review
Health Care Sciences & Services
Francesco Bonomi, Silvia Peretti, Gemma Lepri, Vincenzo Venerito, Edda Russo, Cosimo Bruni, Florenzo Iannone, Sabina Tangaro, Amedeo Amedei, Serena Guiducci, Marco Matucci Cerinic, Silvia Bellando Randone
Summary: Machine learning shows promising applications in systemic sclerosis, including early diagnosis, classification, and treatment prediction, offering new possibilities for precision medicine.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Health Care Sciences & Services
Robert Chrzan, Monika Bociaga-Jasik, Amira Bryll, Anna Grochowska, Tadeusz Popiela
Summary: This study compared automatic assessment of HRCT chest images by artificial intelligence in patients with pneumonia subgroups: COVID-19, bronchopneumonia, and atypical pneumonia. Significant differences were found in inflammation volume and ground glass percentage among the subgroups. However, there was partial overlap between COVID-19 pneumonia and atypical pneumonia, potentially limiting the usefulness of automatic analysis in differentiating the etiology.
JOURNAL OF PERSONALIZED MEDICINE
(2021)
Article
Biochemistry & Molecular Biology
Hwa-Yen Chiu, Rita Huan-Ting Peng, Yi-Chian Lin, Ting-Wei Wang, Ya-Xuan Yang, Ying-Ying Chen, Mei-Han Wu, Tsu-Hui Shiao, Heng-Sheng Chao, Yuh-Min Chen, Yu-Te Wu
Summary: This study presents a machine learning method for early lung cancer detection using chest X-rays and demonstrates its effectiveness in assisting radiologists in the early detection of lung nodules.
Review
Biochemistry & Molecular Biology
Fulvia Ceccarelli, Francesco Natalucci, Licia Picciariello, Claudia Ciancarella, Giulio Dolcini, Angelica Gattamelata, Cristiano Alessandri, Fabrizio Conti
Summary: Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease with diverse immunological features and clinical manifestations, leading to delays in diagnosis and treatment. Machine learning models (MLMs) have shown promise in various aspects of SLE research, such as diagnosis, pathogenesis, disease-related manifestations like Lupus Nephritis, outcomes, treatment, and unique features like pregnancy and quality of life. The review of published data suggests the potential application of MLMs in the SLE scenario.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Viraj Kulkarni, Sanjesh Pawale, Amit Kharat
Summary: This paper explores the integration of a variational quantum circuit into a classical neural network for detecting pneumonia from chest radiographs. The hybrid network outperforms the classical network on different performance measures, and these improvements are statistically significant.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Jianhong Cheng, John Sollee, Celina Hsieh, Hailin Yue, Nicholas Vandal, Justin Shanahan, Ji Whae Choi, Thi My Linh Tran, Kasey Halsey, Franklin Iheanacho, James Warren, Abdullah Ahmed, Carsten Eickhoff, Michael Feldman, Eduardo Mortani Barbosa, Ihab Kamel, Cheng Ting Lin, Thomas Yi, Terrance Healey, Paul Zhang, Jing Wu, Michael Atalay, Harrison X. Bai, Zhicheng Jiao, Jianxin Wang
Summary: Deep learning models using longitudinal CXRs and clinical data were developed to predict in-hospital mortality for COVID-19 patients in the ICU. Models based on pre-ICU CXRs achieved an AUC of 0.632 and an accuracy of 0.593, models based on ICU CXRs achieved an AUC of 0.697 and an accuracy of 0.657, models based on all longitudinal CXRs achieved an AUC of 0.702 and an accuracy of 0.694, and models based on clinical data alone achieved an AUC of 0.653 and an accuracy of 0.657. The addition of longitudinal imaging to clinical data significantly improved mortality prediction, reaching an AUC of 0.727 and an accuracy of 0.732.
EUROPEAN RADIOLOGY
(2022)
Article
Health Care Sciences & Services
Stijn Denissen, Oliver Y. Chen, Johan De Mey, Maarten De Vos, Jeroen Van Schependom, Diana Maria Sima, Guy Nagels
Summary: Machine learning shows promise in predicting cognitive deterioration in multiple sclerosis, but current research mainly focuses on physical deterioration, neglecting cognitive decline. This review introduces machine learning and its pitfalls, important elements for study design, and current literature on cognitive prognosis in multiple sclerosis using machine learning, aiming to advance the field.
JOURNAL OF PERSONALIZED MEDICINE
(2021)
Review
Health Care Sciences & Services
Roberta Fusco, Roberta Grassi, Vincenza Granata, Sergio Venanzio Setola, Francesca Grassi, Diletta Cozzi, Biagio Pecori, Francesco Izzo, Antonella Petrillo
Summary: The study provides an overview of AI and COVID-19 using chest CT and CXR images, emphasizing the high accuracy and precision of AI methods in diagnosing COVID-19. Despite variability, AI approaches show potential in disease identification, case monitoring, outbreak prediction, mortality risk assessment, diagnosis, and management of COVID-19.
JOURNAL OF PERSONALIZED MEDICINE
(2021)
Article
Health Care Sciences & Services
Heui Chul Jung, Changjin Kim, Jaehoon Oh, Tae Hyun Kim, Beomgyu Kim, Juncheol Lee, Jae Ho Chung, Hayoung Byun, Myeong Seong Yoon, Dong Keon Lee
Summary: This study developed an algorithm for multilabel classification of endotracheal tube (ETT) position based on the distance from carina to ETT tip using deep convolutional neural network (CNN) and automatic segmentation. The algorithm achieved good performance in terms of accuracy, precision, sensitivity, specificity, and F1-score, improving physician's decision-making on ETT depth.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Health Care Sciences & Services
Seungkyo Jung, Jaehoon Oh, Jongbin Ryu, Jihoon Kim, Juncheol Lee, Yongil Cho, Myeong Seong Yoon, Ji Young Jeong
Summary: Recent studies have developed an algorithm using deep CNN for the automatic classification and segmentation of the central venous catheter (CVC) position on chest radiography images. The results showed high accuracy and F1-score values, indicating the comparative performance of deep CNN in CVC position classification and automatic segmentation.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Review
Chemistry, Multidisciplinary
Ady Suwardi, FuKe Wang, Kun Xue, Ming-Yong Han, Peili Teo, Pei Wang, Shijie Wang, Ye Liu, Enyi Ye, Zibiao Li, Xian Jun Loh
Summary: Biomaterials research has historically been hindered by long development periods, but the application of machine learning in materials science has greatly accelerated progress. The combination of machine learning with high-throughput theoretical predictions and experiments has shifted the traditional trial and error paradigm to a data-driven paradigm, which is driving the discovery and application of biomaterials.
ADVANCED MATERIALS
(2022)
Review
Clinical Neurology
Fardin Nabizadeh, Elham Ramezannezhad, Amirhosein Kargar, Amir Mohammad Sharafi, Ali Ghaderi
Summary: This study conducted a systematic review and meta-analysis on the role of artificial intelligence (AI) in the diagnosis of multiple sclerosis (MS). The results showed that the use of AI models can improve diagnostic accuracy in MS patients and enhance current diagnostic approaches.
NEUROLOGICAL SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Valerio La Gatta, Vincenzo Moscato, Marco Postiglione, Giancarlo Sperli
Summary: In this paper, a novel model-agnostic Explainable AI technique named CASTLE is proposed to provide rule-based explanations based on both the local and global model's workings. The framework has been evaluated on six datasets in terms of temporal efficiency, cluster quality and model significance, showing a 6% increase in interpretability compared to another state-of-the-art technique, Anchors.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Biochemistry & Molecular Biology
Norman E. Sharpless, Anthony R. Kerlavage
Summary: Artificial intelligence, machine learning, and deep learning have diverse applications in cancer research and clinical care, and the National Cancer Institute (NCI) is actively involved in supporting and advancing these technologies. In addition to developing and evaluating AI tools, NCI focuses on fostering a culture of data sharing, training the next generation of scientists, promoting interdisciplinary collaborations, and ensuring ethical principles in AI research and technologies.
BIOCHIMICA ET BIOPHYSICA ACTA-REVIEWS ON CANCER
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
K. Martini, B. Baessler, M. Bogowicz, C. Bluthgen, M. Mannil, S. Tanadini-Lang, J. Schniering, B. Maurer, T. Frauenfelder
Summary: Texture-based radiomics features can accurately detect interstitial lung disease in patients with systemic sclerosis and distinguish between different disease stages, providing more accurate results than mere visual analysis.
EUROPEAN RADIOLOGY
(2021)
Letter
Chemistry, Applied
Nicola Cicero, Sebastiano Gangemi, Alessandro Allegra
NATURAL PRODUCT RESEARCH
(2023)
Review
Acoustics
Federico Pistoia, Riccardo Picasso, Federico Zaottini, Sara Sanguinetti, Simone Caprioli, Luca Tovt, Michelle Pansecchi, Carlo Martinoli
Summary: The aim of this study is to review the sonographic appearance of facial muscles using high-frequency transducers and to demonstrate a step-by-step scanning technique for effective evaluation. Additionally, it showcases the clinical application of ultrasound in diagnosing pathological cases. Recent technological advancements have greatly enhanced the potential of high-resolution ultrasound in facial evaluation, with an expected increase in future clinical indications.
JOURNAL OF ULTRASOUND IN MEDICINE
(2023)
Review
Chemistry, Applied
Eleonora Di Salvo, Francesca Conte, Marco Casciaro, Sebastiano Gangemi, Nicola Cicero
Summary: Mammalian milk contains various components that have chemical and functional activities, which positively impact human health. In addition to their nutritional value, the biologically active compounds in milk play important roles in physiological and biochemical functions in the human body. Donkey and camel milk contain bioactive molecules that have the potential to benefit human health.
NATURAL PRODUCT RESEARCH
(2023)
Article
Chemistry, Applied
Luca Gammeri, Claudia Panzera, Fabrizio Calapai, Nicola Cicero, Sebastiano Gangemi
Summary: Chronic urticaria is a pathological condition characterized by wheals and angioedema lasting for more than six weeks. Treatment commonly involves antihistamines, but corticosteroids and monoclonal antibodies can also be used. Herbal medicine is an alternative approach, with some herbs possessing anti-inflammatory, anti-allergic, and antioxidant properties.
NATURAL PRODUCT RESEARCH
(2023)
Review
Biochemistry & Molecular Biology
Francesco Borgia, Paolo Custurone, Federica Li Pomi, Mario Vaccaro, Clara Alessandrello, Sebastiano Gangemi
Summary: IL-37 and IL-33 are newly identified cytokines that play a role in various inflammatory conditions. This review aims to collect and organize data from multiple studies to establish a comprehensive understanding of their role. The studies assessed mainly focused on atopic dermatitis and immunologic pathways. The collective data suggests a pro-inflammatory role for IL-33 and an anti-inflammatory role for IL-37, potentially linked in an IL-33/IL-37 axis. Early results indicate that both cytokines may serve as markers of disease activity.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Biochemistry & Molecular Biology
Fabiana Furci, Giuseppe Murdaca, Corrado Pelaia, Egidio Imbalzano, Girolamo Pelaia, Marco Caminati, Alessandro Allegra, Gianenrico Senna, Sebastiano Gangemi
Summary: The airway epithelium is the first line of defense for the lungs against environmental triggers. It releases alarmin cytokines, which mediate inflammation in chronic lung diseases. This review focuses on the role of pulmonary epithelial cells and airway epithelial cell alarmins in driving inflammation and explores the therapeutic potential of targeting these molecules.
Editorial Material
Biochemistry & Molecular Biology
Giuseppe Murdaca, Sebastiano Gangemi
Article
Health Care Sciences & Services
Margherita Zen, Mariele Gatto, Roberto Depascale, Francesca Regola, Micaela Fredi, Laura Andreoli, Franco Franceschini, Maria Letizia Urban, Giacomo Emmi, Fulvia Ceccarelli, Fabrizio Conti, Alessandra Bortoluzzi, Marcello Govoni, Chiara Tani, Marta Mosca, Tania Ubiali, Maria Gerosa, Enrica P. Bozzolo, Valentina Canti, Paolo Cardinaletti, Armando Gabrielli, Giacomo Tanti, Elisa Gremese, Ginevra De Marchi, Salvatore De Vita, Serena Fasano, Francesco Ciccia, Giulia Pazzola, Carlo Salvarani, Simone Negrini, Andrea Di Matteo, Rossella De Angelis, Giovanni Orsolini, Maurizio Rossini, Paola Faggioli, Antonella Laria, Matteo Piga, Alberto Cauli, Salvatore Scarpato, Francesca Wanda Rossi, Amato De Paulis, Enrico Brunetta, Angela Ceribelli, Carlo Selmi, Marcella Prete, Vito Racanelli, Angelo Vacca, Elena Bartoloni, Roberto Gerli, Elisabetta Zanatta, Maddalena Larosa, Francesca Saccon, Andrea Doria, Luca Iaccarino
Summary: This study assessed the efficacy of belimumab in treating joint and skin manifestations in a nationwide cohort of SLE patients. The results showed that belimumab significantly improved joint and skin symptoms and reduced the use of glucocorticoids. A significant proportion of patients who did not achieve complete remission initially achieved remission during follow-up.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Article
Chemistry, Analytical
Lucia Billeci, Chiara Sanmartin, Alessandro Tonacci, Isabella Taglieri, Lorenzo Bachi, Giuseppe Ferroni, Gian Paolo Braceschi, Luigi Odello, Francesca Venturi
Summary: In recent decades, traditional descriptive analysis performed by skilled sensory panels has been deemed too complex and time-consuming for the industry needs, leading to the exploration of more efficient methods of sensory training. This study investigated the effectiveness of a short, intensive sensory training period using wearable sensors to monitor physiological signals related to emotions in a group of wine tasters. The results showed that even a two-day training period could effectively modulate autonomic nervous system activity and familiarize tasters with odorous compounds.
Letter
Cardiac & Cardiovascular Systems
Roberto G. Carbone, Simone Negrini, Francesco Puppo
HEART LUNG AND CIRCULATION
(2023)
Editorial Material
Chemistry, Multidisciplinary
Maurizio Varanini, Alessandro Tonacci, Lucia Billeci
APPLIED SCIENCES-BASEL
(2023)
Article
Pharmacology & Pharmacy
R. G. Carbone, A. Monselise, R. A. Filiberti, D. Penna, S. Negrini, F. Puppo
Summary: The aim of this study was to evaluate the predictive value of New York Heart Association (NYHA) class and systolic pulmonary artery pressure (sPAP) in major interstitial lung diseases (ILD) including idiopathic pulmonary fibrosis (IPF), non-specific interstitial pneumonia (NSIP), hypersensitivity pneumonitis (HP) and other ILD like granulomatosis with polyangiitis (GPA). Analysis of 104 ILD patients showed that NYHA class and sPAP were negatively associated with survival, indicating worse prognosis for IPF and NSIP compared to HP and GPA patients.
EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES
(2023)
Article
Respiratory System
Roberto G. Carbone, Giovanni Bottino, Simone Negrini, Francesco Puppo
Summary: Chronic obstructive pulmonary disease (COPD) is a widely diffuse group of diseases that result in airflow blockage and persistent respiratory symptoms. Forced expiratory flow (FEF25-75) is a useful measurement for early COPD diagnosis. We report a case in which a patient showed no response to LAMA treatment but significant improvement with LAMA-LABA combination therapy. This highlights the importance of FEF25-75 evaluation and the efficacy of LAMA-LABA therapy for small airway obstruction.
RESPIRATORY MEDICINE CASE REPORTS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Simone Caprioli, Alberto Tagliafico, Martina Fiannacca, Fabio Borda, Riccardo Picasso, Cristina Conforti, Alessandro Casaleggio, Giuseppe Cittadini
Summary: Despite the use of antibiotics, deep neck infections remain a clinical problem with potential life-threatening complications. Imaging, particularly computed tomography, plays a crucial role in identifying the source, extent, and complications of these infections. Knowledge of neck anatomy allows radiologists to evaluate the spread of infections and communicate important information to surgeons. This review focuses on the imaging of deep neck infections, highlighting relevant anatomy and clinical scenarios to aid in prompt diagnosis and early recognition of complications.
Article
Computer Science, Artificial Intelligence
Gennaro Tartarisco, Giovanni Cicceri, Roberta Bruschetta, Alessandro Tonacci, Simona Campisi, Salvatore Vitabile, Antonio Cerasa, Salvatore Distefano, Alessio Pellegrino, Pietro Amedeo Modesti, Giovanni Pioggia
Summary: This paper presents a Medical Cyber-Physical System (MCPS) for the automatic classification of heart valve diseases onsite. The proposed system combines different neural network models and has been validated on a new dataset, demonstrating high accuracy and feasibility.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)