A 48-year-old man with no relevant medical history went to a general acute hospital seeking medical attention. He had fever, cough, and chest pain. A chest X-ray revealed pleural effusion, which prompted a puncture and a subsequent culture of the sample; antibiotic treatment was prescribed. Despite the treatment, the man remained febrile, and a new clinical examination suggested a probable onychomycosis of all 20 nails. A rapid HIV test was carried out. The culture from the pleural puncture showed yeast growth identified as Cryptococcus sp., revealing a disseminated disease with central nervous involvement, thus leading to an early diagnosis with a better prognosis.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.riam.2025.01.001 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Integration of novel artificial intelligence tools in pediatric urologic practice.
Curr Opin Urol
March 2025
Department of Pediatric Urology, Oregon Health and Science University, Portland, Oregon, USA.
Purpose Of Review: There has been an explosion of creative uses of artificial intelligence (AI) in healthcare, with AI being touted as a solution for many problems facing the healthcare system. This review focuses on tools currently available to pediatric urologists, previews up-and-coming technologies, and highlights the latest studies investigating benefits and limitations of AI in practice.
Recent Findings: Imaging-driven AI software and clinical prediction tools are two of the more exciting applications of AI for pediatric urologists.
[Urge urinary incontinence in women between 40 and 65 years: prevalence, quality of life, social impact, and costs].
Epidemiol Prev
March 2025
Center for Nursing Research and Innovation (CeNRI), Università Vita-Salute San Raffaele, Milano.
Background: urge urinary incontinence (UUI) is the involuntary loss of urine accompanied or immediately preceded by a sudden and strong desire to urinate that cannot be delayed or that is difficult to postpone. Data claim that UUI increases significantly from 40 to 65 years, which is why this specific age group, which has been little studied in the literature, deserves to be investigated. Moreover, they are socially active and working women who represent a social and economic resource for the country: therefore, their malaise is not only a personal problem, but also a problem for the society.
View Article and Find Full Text PDFA proximal policy optimisation algorithm-based algorithm for cardiovascular disorders detection.
J Med Eng Technol
March 2025
College of Basic Medical, North China University of Science and Technology, Tangshan, China.
Cardiovascular diseases (CVDs) significantly impact athletes, impacting the heart and blood vessels. This article introduces a novel method to assess CVD in athletes through an artificial neural network (ANN). The model utilises the mutual learning-based artificial bee colony (ML-ABC) algorithm to set initial weights and proximal policy optimisation (PPO) to address imbalanced classification.
View Article and Find Full Text PDF"We're all about being together as a family": Community sports program fosters newcomer immigrant girls' academic achievement, resilience, and coping.
Am J Community Psychol
March 2025
Department of Clinical Psychology, Palo Alto University, Palo Alto, California, USA.
Drawing from a liberation psychology framework, this paper describes a community soccer program designed to address inequalities in education, health, and social inclusion among newcomer immigrant girls. The mixed-methods study drew upon youth voices to explore how the program fostered resilience, effective coping, and academic achievement. The study included a quantitative sample (n = 20) and a qualitative sub-sample (n = 13), as well as school-wide comparison data (n = 431).
View Article and Find Full Text PDFArtificial Intelligence in Temporomandibular Joint Disorders: An Umbrella Review.
Clin Exp Dent Res
February 2025
Department of Dental Research Cell, Dr. D. Y. Patil Dental College and Hospital, Dr. D. Y. Patil Vidyapeeth, Pune, India.
Objectives: Given the complexity of temporomandibular joint disorders (TMDs) and their overlapping symptoms with other conditions, an accurate diagnosis necessitates a thorough examination, which can be time-consuming and resource-intensive. Consequently, innovative diagnostic tools are required to increase TMD diagnosis efficiency and precision. Therefore, the purpose of this umbrella review was to examine the existing evidence about the usefulness of artificial intelligence (AI) in TMD diagnosis.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!