AIMC Topic: Deep Learning

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Use of Health Belief Model-based Deep Learning to Understand Public Health Beliefs in Breast Cancer Screening from Social Media before and during the COVID-19 Pandemic.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 11, 2024
Breast cancer is the second leading cause of cancer death for women in the United States. While breast cancer screening participation is the most effective method for early detection, screening rate has remained low. Given that understanding health p...
Social Media COVID-19 Health Belief Model Humans Breast Neoplasms Female Pandemics United States Public Health Deep Learning Early Detection of Cancer
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Evaluating Deep Learning Performance for P300 Neural Signal Classification.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 11, 2024
P300 event-related potential (ERP) signals are useful neurological biomarkers, and their accurate classification is important when studying the cognitive functions in patients with neurological disorders. While many studies have proposed models for c...
Electroencephalography Humans Machine Learning Brain-Computer Interfaces Algorithms Event-Related Potentials, P300 Deep Learning
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Transferable and Interpretable Treatment Effectiveness Prediction for Ovarian Cancer via Multimodal Deep Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 11, 2024
Ovarian cancer, a potentially life-threatening disease, is often difficult to treat. There is a critical need for innovations that can assist in improved therapy selection. Although deep learning models are showing promising results, they are employe...
Ovarian Neoplasms Deep Learning Treatment Outcome Humans Female
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Split Learning for Distributed Collaborative Training of Deep Learning Models in Health Informatics.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 11, 2024
Deep learning continues to rapidly evolve and is now demonstrating remarkable potential for numerous medical prediction tasks. However, realizing deep learning models that generalize across healthcare organizations is challenging. This is due, in par...
Humans Deep Learning Privacy Electronic Health Records Medical Informatics
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Inter-fractional portability of deep learning models for lung target tracking on cine imaging acquired in MRI-guided radiotherapy.

Physical and engineering sciences in medicine Jan 10, 2024
MRI-guided radiotherapy systems enable beam gating by tracking the target on planar, two-dimensional cine images acquired during treatment. This study aims to evaluate how deep-learning (DL) models for target tracking that are trained on data from on...
Algorithms Radiotherapy, Image-Guided Lung Magnetic Resonance Imaging, Cine Image Processing, Computer-Assisted Humans Deep Learning Lung Neoplasms
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An enhanced drought forecasting in coastal arid regions using deep learning approach with evaporation index.

Environmental research Jan 10, 2024
Coastal arid regions are similar to deserts, where it receives significantly less rainfall, less than 10 cm. Perhaps the world's worst natural disaster, coastal area droughts, can only be detected using reliable monitoring systems. Creating a reliabl...
Machine Learning Forecasting Droughts Temperature Deep Learning
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End-to-end volumetric segmentation of white matter hyperintensities using deep learning.

Computer methods and programs in biomedicine Jan 10, 2024
BACKGROUND AND OBJECTIVES: Reliable detection of white matter hyperintensities (WMH) is crucial for studying the impact of diffuse white-matter pathology on brain health and monitoring changes in WMH load over time. However, manual annotation of 3D h...
Algorithms Humans Deep Learning White Matter Magnetic Resonance Imaging Brain Image Processing, Computer-Assisted
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Deep insights into MCI diagnosis: A comparative deep learning analysis of EEG time series.

Journal of neuroscience methods Jan 10, 2024
BACKGROUND: Individuals in the early stages of Alzheimer's Disease (AD) are typically diagnosed with Mild Cognitive Impairment (MCI). MCI represents a transitional phase between normal cognitive function and AD. Electroencephalography (EEG) records c...
Deep Learning Cognitive Dysfunction Humans Neural Networks, Computer Alzheimer Disease Time Factors Electroencephalography
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The BONSAI (Brain and Optic Nerve Study with Artificial Intelligence) deep learning system can accurately identify pediatric papilledema on standard ocular fundus photographs.

Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus Jan 10, 2024
BACKGROUND: Pediatric papilledema often reflects an underlying severe neurologic disorder and may be difficult to appreciate, especially in young children. Ocular fundus photographs are easy to obtain even in young children and in nonophthalmology se...
Child, Preschool Child Fundus Oculi Papilledema Optic Nerve Adult Deep Learning Artificial Intelligence Brain Humans
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Strategies for deep learning-based attenuation and scatter correction of brain F-FDG PET images in the image domain.

Medical physics Jan 10, 2024
BACKGROUND: Attenuation and scatter correction is crucial for quantitative positron emission tomography (PET) imaging. Direct attenuation correction (AC) in the image domain using deep learning approaches has been recently proposed for combined PET/M...
Brain Deep Learning Positron Emission Tomography Computed Tomography Positron-Emission Tomography Fluorodeoxyglucose F18 Image Processing, Computer-Assisted Magnetic Resonance Imaging
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