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A Digital Tool for Clinical Evidence-Driven Guideline Development by Studying Properties of Trial Eligible and Ineligible Populations: Development and Usability Study.
J Med Internet Res
January 2025
Advanced Care Research Centre, Usher Institute, The University of Edinburgh, Edinburgh, United Kingdom.
Background: Clinical guideline development preferentially relies on evidence from randomized controlled trials (RCTs). RCTs are gold-standard methods to evaluate the efficacy of treatments with the highest internal validity but limited external validity, in the sense that their findings may not always be applicable to or generalizable to clinical populations or population characteristics. The external validity of RCTs for the clinical population is constrained by the lack of tailored epidemiological data analysis designed for this purpose due to data governance, consistency of disease or condition definitions, and reduplicated effort in analysis code.
View Article and Find Full Text PDFDDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.
Comput Med Imaging Graph
January 2025
University of Electronic Science and Technology of China, Chengdu, Sichuan, China. Electronic address:
In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusion MRI, namely DDEvENet, for anatomical brain parcellation. The key innovation of DDEvENet is the design of an evidential deep learning framework to quantify predictive uncertainty at each voxel during a single inference. To do so, we design an evidence-based ensemble learning framework for uncertainty-aware parcellation to leverage the multiple dMRI parameters derived from diffusion MRI.
View Article and Find Full Text PDFSurf therapy for people with mental health disorders: a systematic review of randomized and non-randomized controlled trials.
BMC Complement Med Ther
October 2024
Centre for Research, Education, Innovation, and Intervention in Sport (CIFI 2 D), Faculty of Sport, University of Porto (FADEUP), Porto, 4200-450, Portugal.
Background: Surf therapy is gaining popularity for improving mental health. However, there is limited research evidence to substantiate these claims. Therefore, this systematic review aimed to assess randomized or non-randomized studies analyzing the efficacy of surf therapy in improving symptoms of mental illness compared to non-exercising controls and/or alternative intervention, and to identify evidential gaps to inform future research.
View Article and Find Full Text PDFEviD-GAN: Improving GAN With an Infinite Set of Discriminators at Negligible Cost.
IEEE Trans Neural Netw Learn Syst
August 2024
Ensemble learning improves the capability of convolutional neural network (CNN)-based discriminators, whose performance is crucial to the quality of generated samples in generative adversarial network (GAN). However, this learning strategy results in a significant increase in the number of parameters along with computational overhead. Meanwhile, the suitable number of discriminators required to enhance GAN performance is still being investigated.
View Article and Find Full Text PDFEvidence modeling for reliability learning and interpretable decision-making under multi-modality medical image segmentation.
Comput Med Imaging Graph
September 2024
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Computer and Data Science, Case Western Reserve University, Cleveland, OH, USA. Electronic address:
Reliability learning and interpretable decision-making are crucial for multi-modality medical image segmentation. Although many works have attempted multi-modality medical image segmentation, they rarely explore how much reliability is provided by each modality for segmentation. Moreover, the existing approach of decision-making such as the softmax function lacks the interpretability for multi-modality fusion.
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