AIMC Topic: Algorithms

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Multi-scale interaction and locally enhanced bridging network for medical image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jul 22, 2025
Accurate organ segmentation is crucial for precise medical diagnosis. Recent methods in CNNs and Transformers have significantly enhanced automatic medical image segmentation. Their encoders and decoders often rely on simple skip connections, which f...
Humans Tomography, X-Ray Computed Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Algorithms
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SNA-SKAN: Unpaired learning for SDOCT speckle noise removal based on self noise assist and kolmogorov-arnold network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jul 22, 2025
Optical Coherence Tomography (OCT) will inevitably be contaminated by speckle noise when imaging, resulting in a decrease in the visual quality of images and affecting clinical diagnosis. Existing unsupervised denoising methods often rely on complex ...
Signal-To-Noise Ratio Algorithms Wavelet Analysis Humans Image Processing, Computer-Assisted Neural Networks, Computer Tomography, Optical Coherence
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MinT: Magnetic resonance image unsupervised translation via decoupling anatomical structure and contrast.

Computers in biology and medicine Jul 22, 2025
Unsupervised image-to-image translation, which synthesizes new images from existing ones, has become a prominent research topic in computer vision. This technique is particularly valuable in the magnetic resonance (MR) imaging domain, where acquiring...
Unsupervised Machine Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Brain Humans
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Semi-supervised motion flow and myocardial strain estimation in cardiac videos using distance maps and memory networks.

Computers in biology and medicine Jul 22, 2025
Myocardial strain plays a crucial role in diagnosing heart failure and myocardial infarction. Its computation relies on assessing heart muscle motion throughout the cardiac cycle. This assessment can be performed by following key points on each frame...
Humans Algorithms Image Processing, Computer-Assisted Heart Magnetic Resonance Imaging, Cine Male Deep Learning
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Prediction of Fraction Unbound in Human Plasma for Per- and Polyfluoroalkyl Substances: Evaluating Transfer Learning as an Algorithmic Solution to the Problem of Sparse Data.

Journal of chemical information and modeling Jul 22, 2025
Fraction unbound in plasma () is a crucial parameter in physiologically based toxicokinetic (PBTK) models, representing the fraction of a chemical compound that is not sequestered by plasma proteins when present in the bloodstream. This is often used...
Fluorocarbons Quantitative Structure-Activity Relationship Algorithms Deep Learning Humans Machine Learning
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Machine learning in Alzheimer's disease genetics.

Nature communications Jul 22, 2025
Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest Europe...
Neural Networks, Computer Polymorphism, Single Nucleotide Alzheimer Disease Machine Learning Genome-Wide Association Study GTPase-Activating Proteins Algorithms Humans Genetic Predisposition to Disease
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Efficient Compression of Mass Spectrometry Images via Contrastive Learning-Based Encoding.

Analytical chemistry Jul 21, 2025
In this study, we introduce a novel encoding algorithm utilizing contrastive learning to address the substantial data size challenges inherent in mass spectrometry imaging. Our algorithm compresses MSI data into fixed-length vectors, significantly re...
Barrett Esophagus Urinary Bladder Data Compression Image Processing, Computer-Assisted Mice Humans Mass Spectrometry Machine Learning Algorithms Animals
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A novel framework GRCornShot for corn disease detection using few shot learning with prototypical network.

Scientific reports Jul 21, 2025
Precision and timeliness in the detection of plant diseases are important to limit crop losses and maintain global food security. Much work has been performed to detect plant diseases using deep learning methods. However, deep learning techniques dem...
Neural Networks, Computer Zea mays Deep Learning Algorithms Plant Diseases
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Open-source convolutional neural network to classify distal radial fractures according to the AO/OTA classification on plain radiographs.

European journal of trauma and emergency surgery : official publication of the European Trauma Society Jul 21, 2025
PURPOSE: Convolutional Neural Networks (CNNs) have shown promise in fracture detection, but their ability to improve surgeons' inconsistent fracture classification remains unstudied. Therefore, our aim was create and (externally) validate the perform...
Middle Aged Humans Convolutional Neural Networks Neural Networks, Computer Female Radiography Algorithms Aged Adult Radius Fractures Male
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Prevalence of malnutrition and associated factors in Chinese children and adolescents aged 3-14 years using machine learning algorithms.

Journal of global health Jul 21, 2025
BACKGROUND: Child malnutrition represents a critical global public health issue and it is characterised by high prevalence and severe long-term consequences for growth and development. A better understanding of its contributory factors is essential t...
Humans Machine Learning Female Risk Factors Algorithms Child China East Asian People Adolescent Male Child Nutrition Disorders Child, Preschool Prevalence
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