Publications by authors named "D Matranga"
: Stroke is a leading cause of mortality and disability worldwide, ranking as the second most common cause of death and the third in disability-adjusted life-years lost. Ischaemic stroke, which constitutes the majority of cases, poses significant public health and economic challenges. This study evaluates trends in ischaemic stroke hospitalisations in Italy from 2008 to 2022, focusing on differences before and after the COVID-19 pandemic.
View Article and Find Full Text PDFObjective: Oral diseases, specifically malignant lesions, are serious global health concerns requiring early diagnosis for effective treatment. In recent years, deep learning (DL) has emerged as a powerful tool for the automated detection and classification of oral lesions. This research, by conducting a scoping review and meta-analysis, aims to provide an overview of the progress and achievements in the field of automated detection of oral lesions using DL.
View Article and Find Full Text PDFArticle Synopsis
- Acute myeloid leukemia (AML) relapse is a major cause of mortality following allogeneic stem cell transplants, but using Sorafenib for maintenance post-transplant has shown to lower relapse and death rates in FLT3+ AML patients.
- In a study with 29 adult FLT3m AML patients who received allo-SCT, Sorafenib was administered as maintenance therapy after their initial treatment with midostaurin and chemotherapy.
- Results indicated that 62% of patients received Sorafenib; those who did had significantly improved 2-year overall survival (94%) and lower relapse rates (11%) compared to the whole population (76% OS, 28% CIR).
Background: Multiple factors can fuel nurses' intention to leave their employing hospital or their profession. Job dissatisfaction and burnout are contributors to this decision. Sociodemographic and work context factors can also play a role in explaining nurses' intention to leave.
View Article and Find Full Text PDFPurpose: Evaluate the agreement between bone age assessments conducted by two distinct machine learning system and standard Greulich and Pyle method.
Materials And Methods: Carpal radiographs of 225 patients (mean age 8 years and 10 months, SD = 3 years and 1 month) were retrospectively analysed at two separate institutions (October 2018 and May 2022) by both expert radiologists and radiologists in training as well as by two distinct AI software programmes, 16-bit AI and BoneXpert® in a blinded manner.
Results: The bone age range estimated by the 16-bit AI system in our sample varied between 1 year and 1 month and 15 years and 8 months (mean bone age 9 years and 5 months SD = 3 years and 3 months).