International journal of molecular sciences
Feb 13, 2024
Single-cell RNA sequencing (scRNA-seq) data reveal the complexity and diversity of cellular ecosystems and molecular interactions in various biomedical research. Hence, identifying cell types from large-scale scRNA-seq data using existing annotations...
RATIONALE AND OBJECTIVES: To develop and validate a deep learning (DL)-based method for pancreas segmentation on CT and automatic measurement of pancreatic volume in pancreatic cancer.
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progr...
Journal of imaging informatics in medicine
Feb 12, 2024
Lung nodules are generated based on the growth of small and round- or oval-shaped cells in the lung, which are either cancerous or non-cancerous. Accurate segmentation of these nodules is crucial for early detection and diagnosis of lung cancer. Howe...
Journal of imaging informatics in medicine
Feb 12, 2024
Convolutional Neural Networks have been widely applied in medical image segmentation. However, the existence of local inductive bias in convolutional operations restricts the modeling of long-term dependencies. The introduction of Transformer enables...
Neural networks : the official journal of the International Neural Network Society
Feb 12, 2024
The dreaming Hopfield model constitutes a generalization of the Hebbian paradigm for neural networks, that is able to perform on-line learning when "awake" and also to account for off-line "sleeping" mechanisms. The latter have been shown to enhance ...
The relationship between ethics and artificial intelligence in medicine is a crucial and complex topic that falls within its broader context. Ethics in medical artificial intelligence (AI) involves ensuring that technologies are safe, fair, and respe...
. The existing diagnostic paradigm for diabetic retinopathy (DR) greatly relies on subjective assessments by medical practitioners utilizing optical imaging, introducing susceptibility to individual interpretation. This work presents a novel system f...
PURPOSE: This paper proposes a novel self-supervised learning framework that uses model reinforcement, REference-free LAtent map eXtraction with MOdel REinforcement (RELAX-MORE), for accelerated quantitative MRI (qMRI) reconstruction. The proposed me...
There remains a substantial need for a comprehensive assessment of various natural language processing (NLP) algorithms in longitudinal pharmacokinetic/pharmacodynamic (PK/PD) modeling despite recent advances in machine learning in the space of quant...
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