International journal of antimicrobial agents
Apr 19, 2024
OBJECTIVES: Colistin-induced nephrotoxicity prolongs hospitalisation and increases mortality. The study aimed to construct machine learning models to predict colistin-induced nephrotoxicity in patients with multidrug-resistant Gram-negative infection...
PURPOSE: Na MRI can be used to quantify in-vivo tissue sodium concentration (TSC), but the inherently low Na signal leads to long scan times and/or noisy or low-resolution images. Reconstruction algorithms such as compressed sensing (CS) have been pr...
Epigraphy is witnessing a growing integration of artificial intelligence, notably through its subfield of machine learning (ML), especially in tasks like extracting insights from ancient inscriptions. However, scarce labeled data for training ML algo...
OBJECTIVES: To distinguish histological subtypes of renal tumors using radiomic features and machine learning (ML) based on multiphase computed tomography (CT).
Neural networks : the official journal of the International Neural Network Society
Apr 18, 2024
Few-shot Event Detection (FSED) aims to identify novel event types in new domains with very limited annotated data. Previous PN-based (Prototypical Network) joint methods suffer from insufficient learning of token-wise label dependency and inaccurate...
Medical & biological engineering & computing
Apr 18, 2024
A tissue sample is a valuable resource for understanding a patient's symptoms and health status in relation to tumor growth. Recent research seeks to establish a connection between tissue-specific tumor samples and genetic markers (genes). This break...
Medical & biological engineering & computing
Apr 18, 2024
Imagined speech recognition has developed as a significant topic of research in the field of brain-computer interfaces. This innovative technique has great promise as a communication tool, providing essential help to those with impairments. An imagin...
OBJECTIVE: The feasibility of using deep learning in ultrasound imaging to predict the ambulatory status of patients with Duchenne muscular dystrophy (DMD) was previously explored for the first time. The present study further used clustering algorith...
Estimating penetration rates of Jumbo drills is crucial for optimizing underground mining drilling processes, aiming to reduce costs and time. This study investigates various regression and machine learning methods, including Multilayer Perceptron (M...
INTRODUCTION: Semi-quantitative scoring of various parameters in renal biopsy is accepted as an important tool to assess disease activity and prognostication. There are concerns on the impact of interobserver variability in its prognostic utility, ge...
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