AIMC Topic: Deep Learning

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Advancing structure modeling from cryo-EM maps with deep learning.

Biochemical Society transactions Feb 7, 2025
Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of biomolecular structures that are challenging to resolve using conventional methods. Interpreting a cryo-EM map requires accurate modeling of the...
Protein Conformation Deep Learning Proteins Cryoelectron Microscopy Models, Molecular
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Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach.

JMIR medical informatics Feb 7, 2025
BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health implications. Early detection and management are critical to prevent disease progression and complications. Deep learning (DL) models using retinal image...
Urinalysis Female Humans Renal Insufficiency, Chronic Aged Glomerular Filtration Rate Middle Aged Young Adult Adult Retina Deep Learning Male
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A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification.

Scientific reports Feb 7, 2025
Accurately and early diagnosis of melanoma is one of the challenging tasks due to its unique characteristics and different shapes of skin lesions. So, in order to solve this issue, the current study examines various deep learning-based approaches and...
Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Machine Learning Dermoscopy Algorithms Deep Learning Image Processing, Computer-Assisted Melanoma Bayes Theorem Skin Neoplasms
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Deep learning-based prediction of autoimmune diseases.

Scientific reports Feb 7, 2025
Autoimmune Diseases are a complex group of diseases caused by the immune system mistakenly attacking body tissues. Their etiology involves multiple factors such as genetics, environmental factors, and abnormalities in immune cells, making prediction ...
Receptors, Antigen, T-Cell Diabetes Mellitus, Type 1 Autoimmune Diseases Multiple Sclerosis T-Lymphocytes Deep Learning Humans ROC Curve Neural Networks, Computer
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A deep learning approach for automatic 3D segmentation of hip cartilage and labrum from direct hip MR arthrography.

Scientific reports Feb 7, 2025
The objective was to use convolutional neural networks (CNNs) for automatic segmentation of hip cartilage and labrum based on 3D MRI. In this retrospective single-center study, CNNs with a U-Net architecture were used to develop a fully automated seg...
Neural Networks, Computer Retrospective Studies Humans Magnetic Resonance Imaging Hip Joint Cartilage, Articular Arthrography Male Middle Aged Female Young Adult Deep Learning Adult Imaging, Three-Dimensional
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder.

Translational psychiatry Feb 7, 2025
Although the efficacy of pharmacy in the treatment of attention deficit/hyperactivity disorder (ADHD) has been well established, the lack of predictors of treatment response poses great challenges for personalized treatment. The current study employe...
Treatment Outcome Attention Deficit Disorder with Hyperactivity Child Polymorphism, Single Nucleotide Membrane Proteins Deep Learning Adolescent Genome-Wide Association Study Female Male Humans
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Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema.

Scientific reports Feb 7, 2025
Diabetic Macular Edema (DME) is a major complication of diabetic retinopathy characterized by fluid accumulation in the macula, leading to vision impairment. The standard treatment involves anti-VEGF (Vascular Endothelial Growth Factor) therapy, but ...
Deep Learning Angiogenesis Inhibitors Tomography, Optical Coherence Macular Edema Aged Male Middle Aged Vascular Endothelial Growth Factor A Vascular Endothelial Growth Factor Receptor-2 Humans Algorithms Female Diabetic Retinopathy Neural Networks, Computer
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Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses.

Nature communications Feb 7, 2025
Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improving the diagnosis of benign renal masses and distinguishing aggressive cancers from indolent ones is key to better treatment selection. We analyze 132...
Neural Networks, Computer Artificial Intelligence Prospective Studies Tomography, X-Ray Computed Humans Kidney Nomograms Kidney Neoplasms Female Male Aged Middle Aged Adult Deep Learning
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Deep learning aided determination of the optimal number of detectors for photoacoustic tomography.

Biomedical physics & engineering express Feb 7, 2025
Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology...
Photoacoustic Techniques Tomography Image Processing, Computer-Assisted Artifacts Phantoms, Imaging Algorithms Deep Learning Humans Neural Networks, Computer
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A two-branch framework for blood pressure estimation using photoplethysmography signals with deep learning and clinical prior physiological knowledge.

Physiological measurement Feb 7, 2025
This paper presents a novel dual-branch framework for estimating blood pressure (BP) using photoplethysmography (PPG) signals. The method combines deep learning with clinical prior knowledge and models different time periods (morning, afternoon, and ...
Humans Female Photoplethysmography Blood Pressure Determination Blood Pressure Signal Processing, Computer-Assisted Adult Male Deep Learning
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