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Discovering patient groups in sequential electronic healthcare data using unsupervised representation learning.
BMC Med Inform Decis Mak
January 2025
Great Ormond Street Institute of Child Health, University College London, London, UK.
Introduction: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
Design: We applied document embedding algorithms to real-world paediatric intensive care (PICU) EHR data to extract patient-specific features from 1853 patients' PICU journeys using 647 unique lab tests and medication events. We evaluated the clinical utility of the patient features via a K-means clustering analysis.
Identification of strengths and weaknesses of the healthcare system for persons living with rare diseases in Catalonia (Spain), and recommendations to improve its comprehensive attention: the "acERca las enfermedades raras" project.
Orphanet J Rare Dis
January 2025
Laboratory of Neurogenetics and Molecular Medicine, Center for Genomic Sciences in Medicine, Institut de Recerca Sant Joan de Déu, Únicas SJD Center, Hospital Sant Joan de Déu, Barcelona, Spain.
Background: Rare diseases (RDs) are a heterogeneous group of complex and low-prevalence conditions in which the time to establish a definitive diagnosis is often too long. In addition, for most RDs, few to no treatments are available and it is often difficult to find a specialized care team.
Objectives: The project "acERca las enfermedades raras" (in English: "bringing RDs closer") is an initiative primary designed to generate a consensus by a multidisciplinary group of experts to detect the strengths and weaknesses in the public healthcare system concerning the comprehensive care of persons living with a RD (PLWRD) in the region of Catalonia, Spain, where a Network of Clinical Expert Units (Xarxa d'Unitats de Expertesa Clínica or XUEC) was created and is being implemented since 2015.
A Machine Learning Approach Using Topic Modeling to Identify and Assess Experiences of Patients With Colorectal Cancer: Explorative Study.
JMIR Cancer
January 2025
Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands.
Background: The rising number of cancer survivors and the shortage of health care professionals challenge the accessibility of cancer care. Health technologies are necessary for sustaining optimal patient journeys. To understand individuals' daily lives during their patient journey, qualitative studies are crucial.
View Article and Find Full Text PDFCase report: A rollercoaster journey of pemphigus vegetans.
Front Immunol
January 2025
Department of Rheumatology, Shanghai Skin Disease Hospital, Tongji University School of Medicine, Shanghai, China.
Pemphigus vegetans (P Veg), the rarest subtype of pemphigus, is characterized by vegetative plaques, primarily affecting intertriginous areas. The most common autoantibodies target desmoglein 3 (Dsg3). A 60-year-old female patient presented with well-demarcated red vegetative plaques on her feet, vulva, and thigh, accompanied by surrounding pustules.
View Article and Find Full Text PDFBreastfeeding with primary low milk supply: a phenomenological exploration of mothers' lived experiences of postnatal breastfeeding support.
Int Breastfeed J
January 2025
University College Dublin, Dublin, Ireland.
Background: Most women can produce enough milk to exclusively breastfeed. However, a small cohort are prevented from doing so due to a condition known as primary low milk supply. The aim of the study was to provide new insights into how mothers with this condition experience help and support from professionals, volunteer support groups, and partners.
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