INTRODUCTION: Various Machine Learning (ML) models have been used to predict sepsis-associated mortality. We conducted a systematic review to evaluate the methodologies employed in studies to predict mortality among patients with sepsis.
BACKGROUND: Current diagnostic methods cannot effectively distinguish between latent tuberculosis infection (LTBI) and active tuberculosis (ATB). This study aims to explore novel non-invasive diagnostic biomarkers for LTBI and to elucidate possible m...
HPB : the official journal of the International Hepato Pancreato Biliary Association
Jul 25, 2024
BACKGROUND: We sought to assess the impact of various perioperative factors on the risk of severe complications and post-surgical mortality using a novel maching learning technique.
Neural networks : the official journal of the International Neural Network Society
Jul 25, 2024
Graph neural networks (GNN) are widely used in recommendation systems, but traditional centralized methods raise privacy concerns. To address this, we introduce a federated framework for privacy-preserving GNN-based recommendations. This framework al...
Nanobodies, derived from camelids and sharks, offer compact, single-variable heavy-chain antibodies with diverse biomedical potential. This review explores their generation methods, including display techniques on phages, yeast, or bacteria, and comp...
In tool mark identification, there is still a lack of characteristics and methodologies standardization used to analyze and describe sharp force trauma marks on skeletal remains. This study presents a classification method for cut marks on human bone...
Imbalanced classification is a common and difficult task in many medical image analysis applications. However, most existing approaches focus on balancing feature distribution and classifier weights between classes, while ignoring the inner-class het...
OBJECTIVES: Artificial intelligence (AI) tools utilizing machine learning (ML) have gained increasing utility in medicine and academia as a means of enhancing efficiency. ASReview is one such AI program designed to streamline the systematic review pr...
OBJECTIVE: To develop and validate a machine learning (ML) model based on high-frequency ultrasound (HFUS) images with the aim to identify the functional status of parathyroid glands (PTGs) in secondary hyper-parathyroidism (SHPT) patients.
As an integral aspect of health care, digital technology has enabled modelling of complex relationships to detect, screen, diagnose, and predict patient outcomes. With massive data sets, artificial intelligence (AI) can have marked effects on 3 level...
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