VAE-Surv: A novel approach for genetic-based clustering and prognosis prediction in myelodysplastic syndromes.

Background And Objectives: Several computational pipelines for biomedical data have been proposed to stratify patients and to predict their prognosis through survival analysis. However, these analyses are usually performed independently, without integrating the information derived from each of them. Clustering of survival data is an underexplored problem, and current approaches are limited for biomedical applications, whose data are usually heterogeneous and multimodal, with poor scalability for high-dimensionality.

Hidradenocarcinoma of the Chest With Axillary Lymph Node Metastasis: Report of 2 Cases and Systematic Literature Review of a Breast Cancer Mimicker.

Hidradenocarcinoma (HAC) is a rare malignant neoplasm originating from eccrine sweat glands, often presenting diagnostic challenges because of its resemblance to other malignancies, particularly breast cancer when occurring in the chest region. This report describes 2 cases of HAC with axillary lymph node metastasis, both initially misinterpreted clinically. The first case involved a 63-year-old woman with a sternal mass, near the right breast, initially suspected to be a sebaceous cyst.

Eating disorder risks and psychopathological distress in Italian high school adolescents.

Background: Psychopathological disorders are often comorbid diagnosis in eating disorders (EDs). We aimed to assess the presence of psychopathological traits and symptoms associated with EDs in an Italian high school adolescent population.

Methods: A sample of high school adolescents was enrolled, and demographic and clinical data were collected.

MOSAIC: An Artificial Intelligence-Based Framework for Multimodal Analysis, Classification, and Personalized Prognostic Assessment in Rare Cancers.

Purpose: Rare cancers constitute over 20% of human neoplasms, often affecting patients with unmet medical needs. The development of effective classification and prognostication systems is crucial to improve the decision-making process and drive innovative treatment strategies. We have created and implemented MOSAIC, an artificial intelligence (AI)-based framework designed for multimodal analysis, classification, and personalized prognostic assessment in rare cancers.