AIMC Topic: Probability
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Multi-Constraint Latent Representation Learning for Prognosis Analysis Using Multi-Modal Data.
IEEE transactions on neural networks and learning systems
Jul 6, 2023
The Cox proportional hazard model has been widely applied to cancer prognosis prediction. Nowadays, multi-modal data, such as histopathological images and gene data, have advanced this field by providing histologic phenotype and genotype information....
Spatial-Spectral Unified Adaptive Probability Graph Convolutional Networks for Hyperspectral Image Classification.
IEEE transactions on neural networks and learning systems
Jul 6, 2023
In hyperspectral image (HSI) classification task, semisupervised graph convolutional network (GCN)-based methods have received increasing attention. However, two problems still need to be addressed. The first is that the initial graph structure in th...
Dissecting unsupervised learning through hidden Markov modeling in electrophysiological data.
Journal of neurophysiology
Jul 5, 2023
Unsupervised, data-driven methods are commonly used in neuroscience to automatically decompose data into interpretable patterns. These patterns differ from one another depending on the assumptions of the models. How these assumptions affect specific ...
Calibrating ensembles for scalable uncertainty quantification in deep learning-based medical image segmentation.
Computers in biology and medicine
Jun 1, 2023
Uncertainty quantification in automated image analysis is highly desired in many applications. Typically, machine learning models in classification or segmentation are only developed to provide binary answers; however, quantifying the uncertainty of ...
Patient selection for proton therapy using Normal Tissue Complication Probability with deep learning dose prediction for oropharyngeal cancer.
Medical physics
May 4, 2023
BACKGROUND: In cancer care, determining the most beneficial treatment technique is a key decision affecting the patient's survival and quality of life. Patient selection for proton therapy (PT) over conventional radiotherapy (XT) currently entails co...
Deep learning prediction of post-SBRT liver function changes and NTCP modeling in hepatocellular carcinoma based on DGAE-MRI.
Medical physics
Apr 6, 2023
BACKGROUND: Stereotactic body radiation therapy (SBRT) produces excellent local control for patients with hepatocellular carcinoma (HCC). However, the risk of toxicity for normal liver tissue is still a limiting factor. Normal tissue complication pro...
Automatic detection of punctate white matter lesions in infants using deep learning of composite images from two cases.
Scientific reports
Mar 17, 2023
Punctate white matter lesions (PWMLs) in infants may be related to neurodevelopmental outcomes based on the location or number of lesions. This study aimed to assess the automatic detectability of PWMLs in infants on deep learning using composite ima...
HGM-cNet: Integrating hippocampal gray matter probability map into a cascaded deep learning framework improves hippocampus segmentation.
European journal of radiology
Mar 15, 2023
A robust cascaded deep learning framework with integrated hippocampal gray matter (HGM) probability map was developed to improve the hippocampus segmentation (called HGM-cNet) due to its significance in various neuropsychiatric disorders such as Alzh...
Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images.
Physics in medicine and biology
Feb 23, 2023
Tumor segmentation is a fundamental step for radiotherapy treatment planning. To define an accurate segmentation of the primary tumor (GTVp) of oropharyngeal cancer patients (OPC) each image volume is explored slice-by-slice from different orientati...
Impact of perinephric fat volume and the Mayo Adhesive Probability score on time to clamping in robot-assisted partial nephrectomy.
Journal of robotic surgery
Feb 15, 2023
The aim of this study is to evaluate the association of perinephric fat volume (PNFV) and the Mayo Adhesive Probability (MAP) score with time to clamping (TTC) in robot-assisted partial nephrectomy (RAPN). The study subjects consisted of 73 tumors in...
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