BMC medical informatics and decision making
Oct 14, 2025
BACKGROUND: Leishmaniasis, a neglected tropical disease caused by Leishmania protozoan parasites and transmitted by sandflies, poses a significant global health challenge, especially in resource-limited environments. The life cycle of the parasite in...
BACKGROUND: Significant diagnostic delays are common in primary ciliary dyskinesia (PCD), a rare disease that is significantly underdiagnosed. Scalable screening methods could improve early identification and health outcomes.
BMC medical informatics and decision making
Oct 14, 2025
OBJECTIVES: The primary objective was to identify and analyze the factors that impact diabetes awareness and perception among diabetic and non-diabetic participants. The study also sought to assess the effectiveness of current health awareness progra...
BMC medical informatics and decision making
Oct 14, 2025
BACKGROUND: Early prediction of mortality risk within 28 days of admission is crucial for personalized treatment in patients with pulmonary fibrosis (PF). This study aims to develop a predictive model for 28-day mortality risk in PF patients using in...
BACKGROUND: Individuals with metabolic syndrome (MetS) are more prone to depression, which is a significant complication impacting quality of life. This research seeks to create and validate predictive models for assessing depression risk in patients...
OBJECTIVE: To establish and validate a machine learning model using preoperative multi-sequence MRI radiomic features and clinical data to predict pancreatic fistula after pancreaticoduodenectomy (PD).
BACKGROUND: Protein-energy wasting (PEW) is a common complication of patients on maintenance haemodialysis (MHD) and is strongly associated with poor clinical outcomes; early identification and timely nutritional interventions are essential. The aim ...
BACKGROUND: Establishing risk factors associated with severity and prognosis in the early stages of the disease is important to identify patients who need specialized care. Creating new clinical tools to improve health decisions and outcomes in the p...
INTRODUCTION: Difficult intubation is one of the most challenging scenarios to deal with due to increased morbidity and mortality. Machine learning systems can help predict this process in advance. This study aimed to predict whether patients had dif...
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