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http://dx.doi.org/10.1080/00273171.2016.1265433 | DOI Listing |
Ann Surg Oncol
January 2025
Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Background: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of infection. This study aimed to develop a machine-learning model to predict postoperative infection after cytoreductive surgery (CRS) and HIPEC with splenectomy.
Methods: The study enrolled patients in the national TriNetX database and at the Johns Hopkins Hospital (JHH) who underwent splenectomy during CRS/HIPEC from 2010 to 2024.
Sci Prog
January 2025
Department of Industrial Engineering, UiT-The Arctic University of Norway, Narvik, Norway.
Background: Retail involves directly delivering goods and services to end consumers. Natural disasters and epidemics/pandemics have significant potential to disrupt supply chains, leading to shortages, forecasting errors, price increases, and substantial financial strains on retailers. The COVID-19 pandemic highlighted the need for retail sectors to prepare for crisis impacts on sales forecasts by regularly assessing and adjusting sales volumes, consumer behavior, and forecasting models to adapt to changing conditions.
View Article and Find Full Text PDFFront Artif Intell
January 2025
Department of Genetic Engineering, Computational Biology Lab, School of Bioengineering, SRM Institute of Science and Technology, SRM Nagar, Chennai, India.
Cell-penetrating peptides (CPPs) are highly effective at passing through eukaryotic membranes with various cargo molecules, like drugs, proteins, nucleic acids, and nanoparticles, without causing significant harm. Creating drug delivery systems with CPP is associated with cancer, genetic disorders, and diabetes due to their unique chemical properties. Wet lab experiments in drug discovery methodologies are time-consuming and expensive.
View Article and Find Full Text PDFDigit Health
January 2025
Department of Exercise Rehabilitation & Welfare, Gachon University, Incheon, Republic of Korea.
Objective: Sarcopenia, a condition characterized by the progressive loss of skeletal muscle mass and strength, poses significant challenges in research due to missing data. Incomplete datasets undermine the accuracy and reliability of studies, necessitating effective imputation techniques. This study conducts a comparative analysis of three advanced methods-multiple imputation by chained equations (MICE), support vector regression, and K-nearest neighbors (KNN)-to address data completeness issues in sarcopenia research.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Rehabilitation Medicine, The First Affiliated Hospital of Shenzhen University/The Second People's Hospital of Shenzhen, Shenzhen, China.
Objective: This study aims to evaluate key factors influencing the short-term and long-term prognosis of stroke patients, with a particular focus on variables such as body weight, hemoglobin, electrolytes, kidney function, organ function scores, and comorbidities. Stroke poses a significant global health burden, and understanding its prognostic factors is crucial for clinical management.
Methods: This is a retrospective cohort study based on data from the MIMIC-IV database, including stroke patients from 2010 to 2020.
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