AIMC Topic: Benchmarking

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From CNNs to GANs for cross-modality medical image estimation.

Computers in biology and medicine Apr 27, 2022
Cross-modality image estimation involves the generation of images of one medical imaging modality from that of another modality. Convolutional neural networks (CNNs) have been shown to be useful in image-to-image intensity projections, in addition to...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Benchmarking
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Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT.

BMC bioinformatics Apr 21, 2022
BACKGROUND: The abundance of biomedical text data coupled with advances in natural language processing (NLP) is resulting in novel biomedical NLP (BioNLP) applications. These NLP applications, or tasks, are reliant on the availability of domain-speci...
Natural Language Processing Benchmarking Language PubMed Electric Power Supplies
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A Comprehensive Review of Recent Deep Learning Techniques for Human Activity Recognition.

Computational intelligence and neuroscience Apr 20, 2022
Human action recognition is an important field in computer vision that has attracted remarkable attention from researchers. This survey aims to provide a comprehensive overview of recent human action recognition approaches based on deep learning usin...
Neural Networks, Computer Humans Recognition, Psychology Human Activities Deep Learning Benchmarking
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A generative adversarial network for synthetization of regions of interest based on digital mammograms.

Scientific reports Apr 13, 2022
Deep learning (DL) models are becoming pervasive and applicable to computer vision, image processing, and synthesis problems. The performance of these models is often improved through architectural configuration, tweaks, the use of enormous training ...
Female Benchmarking Neural Networks, Computer Mammography Image Processing, Computer-Assisted Humans Breast Neoplasms
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On evaluation metrics for medical applications of artificial intelligence.

Scientific reports Apr 8, 2022
Clinicians and software developers need to understand how proposed machine learning (ML) models could improve patient care. No single metric captures all the desirable properties of a model, which is why several metrics are typically reported to summ...
Humans Software Benchmarking Machine Learning Artificial Intelligence
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Word Embedding Distribution Propagation Graph Network for Few-Shot Learning.

Sensors (Basel, Switzerland) Mar 30, 2022
Few-shot learning (FSL) is of great significance to the field of machine learning. The ability to learn and generalize using a small number of samples is an obvious distinction between artificial intelligence and humans. In the FSL domain, most graph...
Neural Networks, Computer Artificial Intelligence Humans Benchmarking Machine Learning Semantics
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An automated process for supporting decisions in clustering-based data analysis.

Computer methods and programs in biomedicine Mar 24, 2022
BACKGROUND AND OBJECTIVE: Metrics are commonly used by biomedical researchers and practitioners to measure and evaluate properties of individuals, instruments, models, methods, or datasets. Due to the lack of a standardized validation procedure for a...
Data Analysis Humans Cluster Analysis Reproducibility of Results Biological Ontologies Benchmarking
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Single Image Super-Resolution Quality Assessment: A Real-World Dataset, Subjective Studies, and an Objective Metric.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Mar 15, 2022
Numerous single image super-resolution (SISR) algorithms have been proposed during the past years to reconstruct a high-resolution (HR) image from its low-resolution (LR) observation. However, how to fairly compare the performance of different SISR a...
Neural Networks, Computer Algorithms Humans Benchmarking
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Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions.

Current oncology (Toronto, Ont.) Mar 13, 2022
:The purpose of this study was to discriminate between benign and malignant breast lesions through several classifiers using, as predictors, radiomic metrics extracted from CEM and DCE-MRI images. In order to optimize the analysis, balancing and feat...
Benchmarking Mammography Retrospective Studies Humans Magnetic Resonance Imaging Artificial Intelligence Contrast Media
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A clarification of the nuances in the fairness metrics landscape.

Scientific reports Mar 10, 2022
In recent years, the problem of addressing fairness in machine learning (ML) and automatic decision making has attracted a lot of attention in the scientific communities dealing with artificial intelligence. A plethora of different definitions of fai...
Artificial Intelligence Benchmarking Machine Learning Humans
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