Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Feb 13, 2025
PURPOSE: To develop models using different machine learning algorithms to predict high-risk symptom burden clusters in breast cancer patients undergoing chemotherapy, and to determine an optimal model.
This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a BrainChip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Feb 13, 2025
This study presents a novel wearable solution integrating Polymer Optical Fiber (POF) sensors into a knee sleeve to monitor knee flexion/extension (F/E) patterns during walking. POF sensors offer advantages such as flexibility, light weight, and robu...
Images captured in nighttime or low-light environments are often affected by external factors such as noise and lighting. Aiming at the existing image enhancement algorithms tend to overly focus on increasing brightness, while neglecting the enhancem...
This paper introduces an innovative multi-view stereo matching network-the Multi-Step Depth Enhancement Refine Network (MSDER-MVS), aimed at improving the accuracy and computational efficiency of high-resolution 3D reconstruction. The MSDER-MVS netwo...
Despite the outstanding performance of deep learning (DL) models, their interpretability remains a challenging topic. In this study, we address the transparency of DL models in medical image analysis by introducing a novel interpretability method usi...
PURPOSE: To develop a fully AI-based dose estimation model capable of learning and estimating single pencil beam dose distributions, and to verify its performance by testing the model's generalizability on unseen, previously delivered treatment plans...
BACKGROUND: In diabetic retinopathy, precise segmentation of retinal vessels is essential for accurate diagnosis and effective disease management. This task is particularly challenging due to the varying sizes of vessels, their bifurcations, and the ...
Natural Language Processing (NLP) has the potential to revolutionise clinical research utilising Electronic Health Records (EHR) through the automated analysis of unstructured free text. Despite this potential, relatively few applications have entere...
PURPOSE: To determine whether convolutional neural networks (CNN) can classify the severity of central vision loss using fundus autofluorescence (FAF) images and color fundus images of retinitis pigmentosa (RP), and to evaluate the utility of those i...
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