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Prediction of Preeclampsia Using Machine Learning: A Systematic Review.
Cureus
December 2024
Obstetrics and Gynecology, ESI Hospital and Postgraduate Institute of Medical Sciences and Research (PGIMER) Basaidarapur, New Delhi, IND.
Preeclampsia is one of the leading causes of maternal and perinatal morbidity and mortality. Early prediction is the need of the hour so that interventions like aspirin prophylaxis can be started. Nowadays, machine learning (ML) is increasingly being used to predict the disease and its prognosis.
View Article and Find Full Text PDFExploring the adoption of diaphragm and lung ultrasound (DLUS) by physiotherapists, physical therapists, and respiratory therapists: an updated scoping review.
Ultrasound J
January 2025
Physiotherapy Department, Blackpool Teaching Hospitals NHS Foundation Trust, Whinney Heys Road, Blackpool, FY3 8PY, UK.
Background: The adoption of diaphragm and lung ultrasound (DLUS) by physiotherapists, physical therapists, and respiratory therapists ("therapists") to examine and assess the diaphragm and lungs continues to grow. The aim of this updated scoping review is to re-explore and re-collate the evidence around the adoption of DLUS by therapists.
Methods: This scoping review followed the PRISMA-ScR guidelines.
Background Over the past decade, transvaginal ultrasound (TVUS) has revolutionized the diagnosis of deep endometriosis. We can now accurately describe and evaluate lesions in multiple compartments of the pelvis, increasing diagnostic capacity without the need for initial laparoscopy. Recent consensus and publications support the new and growing evidence for this technique.
View Article and Find Full Text PDFDifferences of microbial growth and biofilm formation among periprosthetic joint infection-causing species: an animal study.
Int Microbiol
January 2025
Department of Orthopedics and Traumatology, Ankara University School of Medicine, Ankara, Turkey.
Purpose: The most frequently used surgical procedures for periprosthetic joint infections (PJIs) are debridement, antibiotics, and implant retention (DAIR), as well as single- or two-stage revision arthroplasty. The choice of surgery is made depending on the full maturation of the biofilm layer. The purpose of this study was to evaluate the biofilm formation and microbial growth using common PJI-causing agents and compare its development on the implant surface.
View Article and Find Full Text PDFCXR-LLaVA: a multimodal large language model for interpreting chest X-ray images.
Eur Radiol
January 2025
Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.
Materials And Methods: For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network.
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