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Thermal ocular burns and evaluation of associated limbal stem cell deficiency in the light of global consensus.
Int Ophthalmol
January 2025
Department of Ophthalmology, Ege University Faculty of Medicine, 35100, Bornova, Izmir, Türkiye.
Purpose: The aim of the present study is to examine the demographic data and clinical features of ocular surface injuries due to thermal burns and to evaluate LSCD in the light of global consensus.
Methods: Thirty-three eyes of 20 cases with ocular surface injury due to thermal burn who attended to the clinic between 2012 and 2023 were included in the study. LSCD severity was staged according to the global consensus which was published in 2019.
Upskilling or deskilling? Measurable role of an AI-supported training for radiology residents: a lesson from the pandemic.
Insights Imaging
January 2025
Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy.
Objectives: This article aims to evaluate the use and effects of an artificial intelligence system supporting a critical diagnostic task during radiology resident training, addressing a research gap in this field.
Materials And Methods: We involved eight residents evaluating 150 CXRs in three scenarios: no AI, on-demand AI, and integrated-AI. The considered task was the assessment of a multi-regional severity score of lung compromise in patients affected by COVID-19.
Artificial intelligence for image recognition in diagnosing oral and oropharyngeal cancer and leukoplakia.
Sci Rep
January 2025
Department of Otolaryngology Head and Neck Surgery, Technical University Munich, Munich, Germany.
Visual diagnosis is one of the key features of squamous cell carcinoma of the oral cavity (OSCC) and oropharynx (OPSCC), both subsets of head and neck squamous cell carcinoma (HNSCC) with a heterogeneous clinical appearance. Advancements in artificial intelligence led to Image recognition being introduced recently into large language models (LLMs) such as ChatGPT 4.0.
View Article and Find Full Text PDFBackground And Objective: To assess whether conventional brightness-mode (B-mode) transrectal ultrasound images of the prostate reveal clinically significant cancers with the help of artificial intelligence methods.
Methods: This study included 2986 men who underwent biopsies at two institutions. We trained the PROstate Cancer detection on B-mode transrectal UltraSound images NETwork (ProCUSNet) to determine whether ultrasound can reliably detect cancer.
Identification of the molecular characterization and tumor microenvironment of thoracic inflammatory myofibroblastic tumors.
J Formos Med Assoc
January 2025
Department of Internal Medicine, National Taiwan University Cancer Center, Taipei, Taiwan; Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan. Electronic address:
Background: Inflammatory myofibroblastic tumors (IMTs), rare soft tissue neoplasms, are characterized by a blend of myofibroblastic proliferation and inflammatory features. While generally characterized by slow growth, IMTs can exhibit locally aggressive behavior, and in rare instances, metastasize to distant sites. This study elucidated the clinical characteristics, molecular profile, and tumor microenvironment of thoracic IMTs.
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