Article
Health Care Sciences & Services
Hannah Johns, Julie Bernhardt, Leonid Churilov
Summary: Predicting patient outcomes based on patient characteristics and care processes is common in medical research, but simplifying multifaceted features into scalar variables for statistical analysis may result in a loss of important clinical detail. The limited range of distance-based predictive methods poses a challenge for researchers, who must balance between simplifying features for analysis or using methods that may not fully meet the needs of the analysis problem.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2021)
Article
Oncology
Rodolphe Vallee, Jean-Noel Vallee, Carole Guillevin, Athena Lallouette, Clement Thomas, Guillaume Rittano, Michel Wager, Remy Guillevin, Alexandre Vallee
Summary: The study aims to use machine learning decision tree models applied to perfusion and spectroscopy MRI to classify lymphomas, glioblastomas, and metastases, and identify the underlying key pathophysiological processes involved in the decision-making algorithms of the models.
FRONTIERS IN ONCOLOGY
(2023)
Article
Agronomy
Elzbieta Wojcik-Gront, Marcin Studnicki
Summary: The study evaluated the yield variability of spring and winter triticale in 31 locations across Poland from 2009 to 2017, finding that spring triticale is more influenced by soil quality while winter triticale is more dependent on water availability, suggesting early sowing for spring triticale and consideration of fungicides and growth regulators for winter triticale grown in Poland with periodic excess water.
Article
Health Care Sciences & Services
Shashikant Rathod, Leena Phadke, Uttam Chaskar, Chetankumar Patil
Summary: According to the World Health Organization, one in ten adults will have Type 2 Diabetes Mellitus (T2DM) in the next few years. This study used a combined approach of resting and orthostatic challenge Heart Rate Variability (HRV) measurement with machine learning techniques to evaluate autonomic dysfunction in T2DM patients. The results showed a blunted autonomic response in the T2DM group compared to the control group, and the developed Classification and Regression Tree (CART) model had better performance in detecting autonomic dysfunction in T2DM.
TECHNOLOGY AND HEALTH CARE
(2022)
Article
Engineering, Industrial
Jiyong Choi, Daniel P. de Oliveira, Fernanda Leite
Summary: This research proposes a novel approach using Classification and Regression Trees to capture similarity in capital project benchmarking, specifically in healthcare projects. The trees are constructed by selecting critical and flexible features associated with cost and schedule performance of the projects. The effectiveness of the method is validated through statistical methods and comparative analysis. This new approach allows for more targeted performance comparisons.
JOURNAL OF MANAGEMENT IN ENGINEERING
(2022)
Article
Business, Finance
Koresh Galil, Ami Hauptman, Rosit Levy Rosenboim
Summary: This study utilizes machine learning techniques to predict corporate credit ratings, finding that classification and regression trees and support vector regression have their own advantages in accuracy and interpretability. However, unconstrained models may produce non-monotonic relationships, thus recommending the use of restricted models. Additionally, the importance of company size in credit rating prediction is underscored.
FINANCE RESEARCH LETTERS
(2023)
Article
Chemistry, Multidisciplinary
Shangwen Qu, Ronghua Wang, Jiangbi Hu, Li Yang
Summary: Improper design of bikeway systems can lead to safety risks for cyclists. This study focuses on quantifying cycling workload as a measure of safety and comfort. Through experiments and analysis, a quantitative model for assessing cycling workload is established.
APPLIED SCIENCES-BASEL
(2022)
Article
Public, Environmental & Occupational Health
Rui Zhu, Yun-Hao Zheng, Zi-Han Zhang, Pei-Di Fan, Jun Wang, Xin Xiong
Summary: This study developed a new category scheme for the profile morphology of temporomandibular disorders (TMDs) based on lateral cephalometric morphology. The study identified three subgroups based on cephalometric morphology and built a decision tree model with high prediction accuracy. This proposed category system may supplement the understanding of TMD and benefit the management of TMD treatment.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Chemistry, Analytical
Cukic Milena, Chiara Romano, Francesca De Tommasi, Massimiliano Carassiti, Domenico Formica, Emiliano Schena, Carlo Massaroni
Summary: Heart rate variability (HRV) indexes are useful for various applications and can be retrieved from the heart's electrical activity or mechanical signals recorded from the body's surface. However, the morphology of mechanical signals is strongly affected by body posture. This study investigated the feasibility of estimating HRV indexes from accelerometer and gyroscope data collected with a wearable IMU positioned at the xiphoid level.
Article
Engineering, Geological
Alireza Salimi, Jamal Rostami, Christian Moormann, Jafar Hassanpour
Summary: The study develops models for predicting TBM penetration rate by incorporating the effects of rock type, using field penetration index and machine learning algorithm. The models provide estimated FPIs based on different rock types, rock strength, and rock mass properties, presented in the form of graphs.
ROCK MECHANICS AND ROCK ENGINEERING
(2022)
Article
Computer Science, Information Systems
Ahmad B. Hassanat, Ahmad S. Tarawneh, Samer Subhi Abed, Ghada Awad Altarawneh, Malek Alrashidi, Mansoor Alghamdi
Summary: Due to the bias of most classifiers towards the dominant class, class imbalance is a challenging problem in machine learning. Oversampling and undersampling are commonly used approaches to address this issue, but both have limitations. In this study, researchers proposed a linear time resampling method based on random data partitioning and majority voting rule to tackle this problem. The method achieved comparable performance to other methods in experiments and can be considered for solving machine learning problems with class-imbalanced datasets.
Review
Biochemistry & Molecular Biology
Giuseppe Gancitano, Russel J. Reiter
Summary: The aim of this review is to provide a general overview on the rationale and potential benefits of melatonin for military personnel. Melatonin can help stabilize wounded individuals, especially in battlefield conditions where immediate access to medical care may be limited. It also has the potential to synchronize the neuro-cardio-respiratory systems, contributing to the oscillation of the heartbeat in synchrony with the breath. This field of investigation holds promise for future research.
Article
Engineering, Environmental
Mahshid Oladi, Mohammad Reza Shokri
Summary: This study assessed the impact of oil-related activities on coral reefs using multiple indicators, with bioaccumulation of PAH in coral tissues, live coral cover, and the Sediment Constituent (SEDCON) Index identified as the most robust proxies. The study emphasized the need for routine monitoring and mitigation practices to maintain healthy reefs in the study areas, particularly in locations subjected to PAH pollution.
JOURNAL OF HAZARDOUS MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Majdy M. Eltahir, Lal Hussain, Areej A. Malibari, Mohamed K. Nour, Marwa Obayya, Heba Mohsen, Adil Yousif, Manar Ahmed Hamza
Summary: In this study, an automated system using short-term heart rate variability analysis was proposed to predict and diagnose congestive heart failure. By extracting multimodal features, the nonlinear, nonstationary, and complex dynamics of heart failure can be captured. The results demonstrated that the proposed methodology can provide further in-depth insights for the early diagnosis and prognosis of congestive heart failure.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Analytical
Aline Taoum, Alexis Bisiaux, Florian Tilquin, Yann Le Guillou, Guy Carrault
Summary: Continuous measurement of heart rate variability using wearable devices is important for monitoring physiological status and preventing diseases. This study compared HRV features measured by a commercial device (Bora Band) and reference electrocardiography (ECG), and validated the use of ultra-short-term HRV as a substitute for short-term HRV features. The results showed agreement between PPG and ECG recordings for most HRV features, and the Bora Band provided valid and reliable HRV measurements in both short and ultra-short-term recordings.
Review
Radiology, Nuclear Medicine & Medical Imaging
Federico Bruno, Domenico Albano, Andrea Agostini, Massimo Benenati, Roberto Cannella, Damiano Caruso, Michaela Cellina, Diletta Cozzi, Ginevra Danti, Federica De Muzio, Francesco Gentili, Giuliana Giacobbe, Salvatore Gitto, Giulia Grazzini, Irene Grazzini, Carmelo Messina, Anna Palmisano, Pierpaolo Palumbo, Alessandra Bruno, Francesca Grassi, Roberta Grassi, Roberta Fusco, Vincenza Granata, Andrea Giovagnoni, Vittorio Miele, Antonio Barile
Summary: Metabolic and overload disorders are rare but important diseases that affect different organs and tissues. Imaging plays a crucial role in early detection and accurate diagnosis, especially in specific organs involved in metabolic pathways. MRI is particularly useful due to its multiparametric properties, but advanced imaging techniques may also be required for accurate characterization and quantification. This review aims to describe the various alterations resulting from these disorders and their imaging findings.
JAPANESE JOURNAL OF RADIOLOGY
(2023)
Review
Biology
Vincenza Granata, Roberta Fusco, Federica De Muzio, Carmen Cutolo, Francesca Grassi, Maria Chiara Brunese, Igino Simonetti, Orlando Catalano, Michela Gabelloni, Silvia Pradella, Ginevra Danti, Federica Flammia, Alessandra Borgheresi, Andrea Agostini, Federico Bruno, Pierpaolo Palumbo, Alessandro Ottaiano, Francesco Izzo, Andrea Giovagnoni, Antonio Barile, Nicoletta Gandolfo, Vittorio Miele
Summary: The only cure for intrahepatic cholangiocarcinoma (iCCA) is surgical resection, and early diagnosis is crucial for improving survival. Artificial Intelligence models can help assess high-risk patients, leading to better diagnosis. Therefore, identifying high-risk patients and utilizing non-invasive screening methods are important.
Article
Medical Informatics
Martina Andellini, Salman Haleem, Massimiliano Angelini, Matteo Ritrovato, Riccardo Schiaffini, Ernesto Iadanza, Leandro Pecchia
Summary: This study aims to validate an artificial intelligence-based algorithm for detecting glycaemic events using ECG signals collected through a non-invasive device. T1D paediatric participants who already use CGM will wear an additional non-invasive wearable device to record physiological data and respiratory rate.
HEALTH AND TECHNOLOGY
(2023)
Article
Medical Informatics
Ernesto Iadanza, Giammarco Pasqua, Davide Piaggio, Corrado Caputo, Monica Gherardelli, Leandro Pecchia
Summary: The study aimed to design, prototype, and test a new device that can connect users with common-use or medical-use interfaces to minimize the risk of infection from contact with contaminated surfaces. The device was successfully developed using UML schemes and a risk analysis, and it included a programmed micro-controller linked to a mobile app. This prototype opens up possibilities for further research in pandemic emergency management.
HEALTH AND TECHNOLOGY
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Antonio Galluzzo, Sofia Boccioli, Ginevra Danti, Federica De Muzio, Michela Gabelloni, Roberta Fusco, Alessandra Borgheresi, Vincenza Granata, Andrea Giovagnoni, Nicoletta Gandolfo, Vittorio Miele
Summary: Gastrointestinal stromal tumours, originating from Cajal cells, are rare neoplasms in the gastroenteric tract. Diagnosis is mainly done through endoscopy, echoendoscopy, computed tomography, magnetic resonance imaging, and positron emission tomography. Radiomics, an emerging technique, can extract invisible medical imaging information and convert it into quantitative data, improving diagnosis, treatment, and prognosis of these tumors.
JAPANESE JOURNAL OF RADIOLOGY
(2023)
Review
Oncology
Vincenza Granata, Roberta Fusco, Sergio Venanzio Setola, Roberta Galdiero, Nicola Maggialetti, Renato Patrone, Alessandro Ottaiano, Guglielmo Nasti, Lucrezia Silvestro, Antonio Cassata, Francesca Grassi, Antonio Avallone, Francesco Izzo, Antonella Petrillo
Summary: In this narrative review, the role of radiomics in assessing prognostic features for liver metastases patients is discussed. Radiomics analysis allows the assessment of textural characteristics in radiological images, which can provide biological data without invasive procedures. However, issues such as poor standardization, reproducibility, and clinical study results hamper the translation of radiomics analysis into clinical practice.
INFECTIOUS AGENTS AND CANCER
(2023)
Review
Medicine, General & Internal
Francesca Grassi, Vincenza Granata, Roberta Fusco, Federica De Muzio, Carmen Cutolo, Michela Gabelloni, Alessandra Borgheresi, Ginevra Danti, Carmine Picone, Andrea Giovagnoni, Vittorio Miele, Nicoletta Gandolfo, Antonio Barile, Valerio Nardone, Roberta Grassi
Summary: The role of radiotherapy in the treatment of lung neoplasms, along with surgery and systemic therapies, has become essential. The focus has shifted towards improving survival outcomes, quality of life, treatment compliance, and management of side effects. Imaging plays a crucial role in evaluating treatment efficacy and identifying rare effects, especially when multiple treatments are involved. Radiation recall pneumonitis, a rare complication, needs to be recognized and characterized accurately, requiring prompt identification and the best therapeutic strategy for minimal disruption of ongoing cancer treatment. Artificial intelligence could play a critical role in this regard, provided a larger patient dataset is available.
JOURNAL OF CLINICAL MEDICINE
(2023)
Review
Medicine, General & Internal
Federica De Muzio, Roberta Fusco, Carmen Cutolo, Giuliana Giacobbe, Federico Bruno, Pierpaolo Palumbo, Ginevra Danti, Giulia Grazzini, Federica Flammia, Alessandra Borgheresi, Andrea Agostini, Francesca Grassi, Andrea Giovagnoni, Vittorio Miele, Antonio Barile, Vincenza Granata
Summary: Rectal cancer is a highly lethal malignancy and surgery is the most common treatment option. The choice of surgical approach aims to maximize function while minimizing the risk of recurrence, and is determined by a multidisciplinary team assessing patient and tumor characteristics. Total mesorectal excision, including both low anterior resection and abdominoperineal resection, remains the standard of care for rectal cancer. Rating: 8 out of 10.
JOURNAL OF CLINICAL MEDICINE
(2023)
Review
Medicine, General & Internal
Carmine Picone, Roberta Fusco, Michele Tonerini, Salvatore Claudio Fanni, Emanuele Neri, Maria Chiara Brunese, Roberta Grassi, Ginevra Danti, Antonella Petrillo, Mariano Scaglione, Nicoletta Gandolfo, Andrea Giovagnoni, Antonio Barile, Vittorio Miele, Claudio Granata, Vincenza Granata
Summary: In modern clinical practice, imaging techniques are increasingly used in emergencies, leading to a higher frequency of examinations and increased radiation exposure. The management of pregnant women is particularly critical as they are at higher risk. While ultrasound and magnetic resonance imaging are preferred, computed tomography remains necessary in certain cases. Protocol optimization is crucial in reducing risks. This review aims to evaluate different diagnostic tools and protocols to control radiation dose in emergency conditions involving abdominal pain and trauma.
JOURNAL OF CLINICAL MEDICINE
(2023)
Review
Imaging Science & Photographic Technology
Francesca Angelone, Alfonso Maria Ponsiglione, Carlo Ricciardi, Giuseppe Cesarelli, Mario Sansone, Francesco Amato
Summary: In addition to their use for obtaining 3D digital dental models, intraoral scanners (IOSs) have recently shown promise as tools for oral health diagnostics. This review examined the literature on the applications of IOSs as detection systems for oral cavity pathologies, highlighting their potential in areas such as tooth wear, caries, plaques, periodontal defects, and other complications. However, there is limited clinical evidence for the use of IOSs as oral health probes, and further validation is needed.
JOURNAL OF IMAGING
(2023)
Review
Computer Science, Information Systems
Alessio Luschi, Camilla Petraccone, Giuseppe Fico, Leandro Pecchia, Ernesto Iadanza
Summary: This study aims to identify and analyze available ontologies that can depict all the available use-cases describing the hospital environment in relation to the European project ODIN. A total of 32 articles were analyzed, resulting in 34 ontologies. The results will lead to the implementation of an integrated ontology that can facilitate data exchange and interconnections among healthcare entities, people, devices, and applications.
Review
Radiology, Nuclear Medicine & Medical Imaging
Fabio Pellegrino, Vincenza Granata, Roberta Fusco, Francesca Grassi, Salvatore Tafuto, Luca Perrucci, Giulia Tralli, Mariano Scaglione
Summary: Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are a heterogeneous group of tumors that arise from cells of the diffuse neuroendocrine system. They can be sporadic or occur in the context of genetic syndromes. They are mostly nonfunctioning, but some produce hormones responsible for clinical syndromes. The grade and differentiation of the tumor can affect clinical behaviors and prognoses. Diagnosis of GEP-NENs involves identifying the presence of the tumor and determining the primary site and extent of metastases. Morphological evaluations, such as CT and MRI, and functional evaluations, such as PET-CT and somatostatin analogs, are important in the diagnostic management of patients.
Article
Radiology, Nuclear Medicine & Medical Imaging
Vincenza Granata, Roberta Fusco, Diletta Cozzi, Ginevra Danti, Lorenzo Faggioni, Duccio Buccicardi, Roberto Prost, Riccardo Ferrari, Margherita Trinci, Michele Galluzzo, Francesca Iacobellis, Mariano Scaglione, Michele Tonerini, Francesca Coppola, Chandra Bortolotto, Damiano Caruso, Eleonora Ciaghi, Michela Gabelloni, Marco Rengo, Giuliana Giacobbe, Francesca Grassi, Luigia Romano, Antonio Pinto, Ferdinando Caranci, Elena Bertelli, Paolo D'Andrea, Emanuele Neri, Andrea Giovagnoni, Roberto Grassi, Vittorio Miele
Summary: This study developed a structured reporting template for whole-body CT examinations of polytrauma patients based on consensus among emergency radiology experts. The template includes four sections with a total of 118 items. In the second round of Delphi method, experts gave higher scores and showed higher agreement compared to the first round.
Article
Oncology
Mario Sansone, Roberta Fusco, Francesca Grassi, Gianluca Gatta, Maria Paola Belfiore, Francesca Angelone, Carlo Ricciardi, Alfonso Maria Ponsiglione, Francesco Amato, Roberta Galdiero, Roberta Grassi, Vincenza Granata, Roberto Grassi
Summary: The study aims to develop mammographic image processing techniques for the extraction of indicators indicative of breast density (BD) risk factors. The results show that machine learning techniques can classify breasts, with the best classifier being the Support Vector Machine (SVM) with an accuracy of 93.55%, true positive rate of 94.44%, and true negative rate of 92.31%. The SVM with 7 selected features by a wrapper method achieves an accuracy of 0.95, sensitivity of 0.96, and specificity of 0.90 in the external validation cohort. Conclusion: Radiomics analysis and machine learning approach can objectively identify breast density.
