AIMC Topic: Humans

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Learning on manifolds without manifold learning.

Neural networks : the official journal of the International Neural Network Society Oct 1, 2024
Function approximation based on data drawn randomly from an unknown distribution is an important problem in machine learning. The manifold hypothesis assumes that the data is sampled from an unknown submanifold of a high dimensional Euclidean space. ...
Algorithms Neural Networks, Computer Machine Learning Humans
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MemberShield: A framework for federated learning with membership privacy.

Neural networks : the official journal of the International Neural Network Society Oct 1, 2024
Federated Learning (FL) allows multiple data owners to build high-quality deep learning models collaboratively, by sharing only model updates and keeping data on their premises. Even though FL offers privacy-by-design, it is vulnerable to membership ...
Neural Networks, Computer Algorithms Deep Learning Humans Privacy Computer Security
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Rethinking deep clustering paradigms: Self-supervision is all you need.

Neural networks : the official journal of the International Neural Network Society Oct 1, 2024
The recent advances in deep clustering have been made possible by significant progress in self-supervised and pseudo-supervised learning. However, the trade-off between self-supervision and pseudo-supervision can give rise to three primary issues. Th...
Humans Neural Networks, Computer Algorithms Deep Learning Supervised Machine Learning Cluster Analysis
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Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society Oct 1, 2024
Many models using the aid of artificial intelligence have been recently proposed to predict the progression of knee osteoarthritis. However, previous models have not been properly validated with an external data set or have reported poor predictive p...
Osteoarthritis, Knee Retrospective Studies Female Humans Disease Progression Male Machine Learning Radiography Middle Aged Aged
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AutoLNMNet: Automated Network for Estimating Lymph-Node Metastasis in EGC Using a Pyramid Vision Transformer and Data Derived From Multiphoton Microscopy.

Microscopy research and technique Oct 1, 2024
Lymph-node status is important in decision-making during early gastric cancer (EGC) treatment. Currently, endoscopic submucosal dissection is the mainstream treatment for EGC. However, it is challenging for even experienced endoscopists to accurately...
Humans Stomach Neoplasms Lymph Nodes Lymphatic Metastasis Microscopy, Fluorescence, Multiphoton ROC Curve Image Processing, Computer-Assisted Deep Learning
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Employing Machine Learning Models to Predict Potential α-Glucosidase Inhibitory Plant Secondary Metabolites Targeting Type-2 Diabetes and Their Validation.

Journal of chemical information and modeling Oct 1, 2024
The need for new antidiabetic drugs is evident, considering the ongoing global burden of type-2 diabetes mellitus despite notable progress in drug discovery from laboratory research to clinical application. This study aimed to build machine learning ...
Humans Diabetes Mellitus, Type 2 Hypoglycemic Agents Machine Learning Glycoside Hydrolase Inhibitors Secondary Metabolism Plants alpha-Glucosidases
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Using machine learning modeling to identify childhood abuse victims on the basis of personality inventory responses.

Journal of psychiatric research Oct 1, 2024
Trauma is very common and associated with significant co-morbidity world-wide, particularly PTSD and frequently other mental health disorders. However, it can be challenging to identify victims of abuse as self-reports can be difficult to elicit due ...
Child Female Male Personality Inventory Humans Child Abuse Adolescent Machine Learning
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Development of learning-based predictive models for radiation-induced atrial fibrillation in non-small cell lung cancer patients by integrating patient-specific clinical, dosimetry, and diagnostic information.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Oct 1, 2024
BACKGROUND AND PURPOSE: Radiotherapy (RT) in non-small cell lung cancer (NSCLC) can induce cardiac adverse events, including atrial fibrillation (AF), despite advanced RT. This study integrates patient-specific information to develop learning-based m...
Radiation Injuries Male Middle Aged Deep Learning Humans Atrial Fibrillation Female Lung Neoplasms Radiotherapy Dosage Aged Machine Learning Chemoradiotherapy Carcinoma, Non-Small-Cell Lung
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Adaptive wavelet-VNet for single-sample test time adaptation in medical image segmentation.

Medical physics Oct 1, 2024
BACKGROUND: In medical image segmentation, a domain gap often exists between training and testing datasets due to different scanners or imaging protocols, which leads to performance degradation in deep learning-based segmentation models. Given the hi...
Wavelet Analysis Deep Learning Time Factors Image Processing, Computer-Assisted Humans
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Multi-instance learning for identifying high-risk subregions associated with synchronous distant metastasis in clear cell renal cell carcinoma.

Medical physics Oct 1, 2024
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most common histological subtypes of renal tumors.
Risk Carcinoma, Renal Cell Support Vector Machine Neoplasm Metastasis Kidney Neoplasms Tomography, X-Ray Computed Middle Aged Female Image Processing, Computer-Assisted Machine Learning Humans Aged Adult Male
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