Supervised Machine Learning

Self-supervised learning for characterising histomorphological diversity and spatial RNA expression prediction across 23 human tissue types.

Nature communications Jul 13, 2024

As vast histological archives are digitised, there is a pressing need to be able to associate specific tissue substructures and incident pathology to disease outcomes without arduous annotation. Here, we learn self-supervised representations using a ...

Image Processing, Computer-Assisted Supervised Machine Learning Gene Expression Profiling Organ Specificity RNA Humans

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ScribSD+: Scribble-supervised medical image segmentation based on simultaneous multi-scale knowledge distillation and class-wise contrastive regularization.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jul 9, 2024

Despite that deep learning has achieved state-of-the-art performance for automatic medical image segmentation, it often requires a large amount of pixel-level manual annotations for training. Obtaining these high-quality annotations is time-consuming...

Image Processing, Computer-Assisted Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Pregnancy Humans Female Algorithms Deep Learning Supervised Machine Learning

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Gradient-based optimization for quantum architecture search.

Neural networks : the official journal of the International Neural Network Society Jul 8, 2024

Quantum Architecture Search (QAS) has shown significant promise in designing quantum circuits for Variational Quantum Algorithms (VQAs). However, existing QAS algorithms primarily explore circuit architectures within a discrete space, which is inhere...

Neural Networks, Computer Supervised Machine Learning Quantum Theory Algorithms Computer Simulation

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A Human-Machine Agent Based on Active Reinforcement Learning for Target Classification in Wargame.

IEEE transactions on neural networks and learning systems Jul 8, 2024

To meet the requirements of high accuracy and low cost of target classification in modern warfare, and lay the foundation for target threat assessment, the article proposes a human-machine agent for target classification based on active reinforcement...

Humans Neural Networks, Computer Supervised Machine Learning Man-Machine Systems Reinforcement, Psychology Algorithms Computer Simulation Machine Learning

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Masked cross-domain self-supervised deep learning framework for photoacoustic computed tomography reconstruction.

Neural networks : the official journal of the International Neural Network Society Jul 7, 2024

Accurate image reconstruction is crucial for photoacoustic (PA) computed tomography (PACT). Recently, deep learning has been used to reconstruct PA images with a supervised scheme, which requires high-quality images as ground truth labels. However, p...

Algorithms Tomography, X-Ray Computed Animals Neural Networks, Computer Mice Supervised Machine Learning Deep Learning Photoacoustic Techniques Image Processing, Computer-Assisted

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Improving prediction of blood cancer using leukemia microarray gene data and Chi2 features with weighted convolutional neural network.

Scientific reports Jul 7, 2024

Blood cancer has emerged as a growing concern over the past decade, necessitating early diagnosis for timely and effective treatment. The present diagnostic method, which involves a battery of tests and medical experts, is costly and time-consuming. ...

Machine Learning Algorithms Hematologic Neoplasms Humans Neural Networks, Computer Oligonucleotide Array Sequence Analysis Leukemia Gene Expression Profiling Supervised Machine Learning

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CPSS: Fusing consistency regularization and pseudo-labeling techniques for semi-supervised deep cardiovascular disease detection using all unlabeled electrocardiograms.

Computer methods and programs in biomedicine Jul 4, 2024

BACKGROUND AND OBJECTIVE: Deep learning usually achieves good performance in the supervised way, which requires a large amount of labeled data. However, manual labeling of electrocardiograms (ECGs) is laborious that requires much medical knowledge. S...

Unsupervised Machine Learning Supervised Machine Learning Cardiovascular Diseases Humans Deep Learning Electrocardiography Algorithms Databases, Factual

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Unsupervised and semi-supervised domain adaptation networks considering both global knowledge and prototype-based local class information for Motor Imagery Classification.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2024

The non-stationarity of EEG signals results in variability across sessions, impeding model building and data sharing. In this paper, we propose a domain adaptation method called GPL, which simultaneously considers global knowledge and prototype-based...

Electroencephalography Supervised Machine Learning Brain-Computer Interfaces Brain Unsupervised Machine Learning Imagination Neural Networks, Computer Algorithms Humans

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Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers With Partially Annotated Ultrasound Images.

IEEE transactions on medical imaging Jul 1, 2024

Deep learning (DL) has proven highly effective for ultrasound-based computer-aided diagnosis (CAD) of breast cancers. In an automatic CAD system, lesion detection is critical for the following diagnosis. However, existing DL-based methods generally r...

Image Interpretation, Computer-Assisted Breast Supervised Machine Learning Algorithms Female Deep Learning Humans Ultrasonography, Mammary Breast Neoplasms

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