AIMC Topic: Benchmarking

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Comparison and benchmark of deep learning methods for non-coding RNA classification.

PLoS computational biology Sep 12, 2024
The involvement of non-coding RNAs in biological processes and diseases has made the exploration of their functions crucial. Most non-coding RNAs have yet to be studied, creating the need for methods that can rapidly classify large sets of non-coding...
Computational Biology Benchmarking RNA, Untranslated Algorithms Deep Learning Humans
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SpeechBrain-MOABB: An open-source Python library for benchmarking deep neural networks applied to EEG signals.

Computers in biology and medicine Sep 11, 2024
Deep learning has revolutionized EEG decoding, showcasing its ability to outperform traditional machine learning models. However, unlike other fields, EEG decoding lacks comprehensive open-source libraries dedicated to neural networks. Existing tools...
Neural Networks, Computer Software Humans Electroencephalography Signal Processing, Computer-Assisted Benchmarking Brain Deep Learning
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Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions.

PLoS computational biology Aug 26, 2024
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. In animals, this regulation is achieved via base-pairing with partially complementary sequences on mainly 3' UTR region of messenger RNAs (mRNAs). Comp...
MicroRNAs Benchmarking Animals Computational Biology RNA, Messenger Machine Learning Algorithms Humans
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Benchmarking brain-computer interface algorithms: Riemannian approaches vs convolutional neural networks.

Journal of neural engineering Aug 21, 2024
To date, a comprehensive comparison of Riemannian decoding methods with deep convolutional neural networks for EEG-based brain-computer interfaces remains absent from published work. We address this research gap by using MOABB, The Mother Of All BCI ...
Evoked Potentials, Visual Imagination Electroencephalography Neural Networks, Computer Benchmarking Algorithms Brain-Computer Interfaces Humans
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Benchmarking robustness of deep neural networks in semantic segmentation of fluorescence microscopy images.

BMC bioinformatics Aug 20, 2024
BACKGROUND: Fluorescence microscopy (FM) is an important and widely adopted biological imaging technique. Segmentation is often the first step in quantitative analysis of FM images. Deep neural networks (DNNs) have become the state-of-the-art tools f...
Microscopy, Fluorescence Benchmarking Semantics Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans
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Navigation benchmarking for autonomous mobile robots in hospital environment.

Scientific reports Aug 7, 2024
The widespread adoption of robotic technologies in healthcare has opened up new perspectives for enhancing accuracy, effectiveness and quality of medical procedures and patients' care. Special attention has been given to the reliability of robots whe...
Humans Hospitals Benchmarking Robotics
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MedExpQA: Multilingual benchmarking of Large Language Models for Medical Question Answering.

Artificial intelligence in medicine Jul 31, 2024
Large Language Models (LLMs) have the potential of facilitating the development of Artificial Intelligence technology to assist medical experts for interactive decision support. This potential has been illustrated by the state-of-the-art performance ...
Artificial Intelligence Natural Language Processing Humans Multilingualism Benchmarking
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NKUT: Dataset and Benchmark for Pediatric Mandibular Wisdom Teeth Segmentation.

IEEE journal of biomedical and health informatics Jun 6, 2024
Germectomy is a common surgery in pediatric dentistry to prevent the potential dangers caused by impacted mandibular wisdom teeth. Segmentation of mandibular wisdom teeth is a crucial step in surgery planning. However, manually segmenting teeth and b...
Algorithms Databases, Factual Child Molar, Third Deep Learning Humans Mandible Benchmarking Datasets as Topic Cone-Beam Computed Tomography Imaging, Three-Dimensional
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Development and benchmarking of a Deep Learning-based MRI-guided gross tumor segmentation algorithm for Radiomics analyses in extremity soft tissue sarcomas.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology May 22, 2024
BACKGROUND: Volume of interest (VOI) segmentation is a crucial step for Radiomics analyses and radiotherapy (RT) treatment planning. Because it can be time-consuming and subject to inter-observer variability, we developed and tested a Deep Learning-b...
Soft Tissue Neoplasms Radiotherapy Planning, Computer-Assisted Extremities Benchmarking Sarcoma Radiomics Female Male Humans Aged Deep Learning Algorithms Adult Magnetic Resonance Imaging Middle Aged
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A whole-slide foundation model for digital pathology from real-world data.

Nature May 22, 2024
Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important ...
Datasets as Topic Pathology, Clinical Image Processing, Computer-Assisted Benchmarking Female Male Neoplasms Humans Machine Learning
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