AIMC Topic: Benchmarking

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Benchmarking clinical risk prediction algorithms with ensemble machine learning for the noninvasive diagnosis of liver fibrosis in NAFLD.

Hepatology (Baltimore, Md.) Apr 30, 2024
BACKGROUND AND AIMS: Ensemble machine-learning methods, like the superlearner, combine multiple models into a single one to enhance predictive accuracy. Here we explore the potential of the superlearner as a benchmarking tool for clinical risk predic...
Adult Male Algorithms Female Liver Cirrhosis Benchmarking Non-alcoholic Fatty Liver Disease Middle Aged Risk Assessment Humans Machine Learning
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DeepSeq2Drug: An expandable ensemble end-to-end anti-viral drug repurposing benchmark framework by multi-modal embeddings and transfer learning.

Computers in biology and medicine Apr 17, 2024
Drug repurposing is promising in multiple scenarios, such as emerging viral outbreak controls and cost reductions of drug discovery. Traditional graph-based drug repurposing methods are limited to fast, large-scale virtual screens, as they constrain ...
Drug Repositioning Benchmarking Deep Learning Antiviral Agents Humans Software
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The limitations of automatically generated curricula for continual learning.

PloS one Apr 16, 2024
In many applications, artificial neural networks are best trained for a task by following a curriculum, in which simpler concepts are learned before more complex ones. This curriculum can be hand-crafted by the engineer or optimised like other hyperp...
Curriculum Upper Extremity Neural Networks, Computer Benchmarking Education, Continuing Humans
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Cataract-1K Dataset for Deep-Learning-Assisted Analysis of Cataract Surgery Videos.

Scientific data Apr 12, 2024
In recent years, the landscape of computer-assisted interventions and post-operative surgical video analysis has been dramatically reshaped by deep-learning techniques, resulting in significant advancements in surgeons' skills, operation room managem...
Benchmarking Video Recording Cataract Extraction Cataract Neural Networks, Computer Deep Learning Humans
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SwinPA-Net: Swin Transformer-Based Multiscale Feature Pyramid Aggregation Network for Medical Image Segmentation.

IEEE transactions on neural networks and learning systems Apr 4, 2024
The precise segmentation of medical images is one of the key challenges in pathology research and clinical practice. However, many medical image segmentation tasks have problems such as large differences between different types of lesions and similar...
Image Processing, Computer-Assisted Benchmarking Semantics Neural Networks, Computer Learning
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Responses of Five Different Artificial Intelligence Chatbots to the Top Searched Queries About Erectile Dysfunction: A Comparative Analysis.

Journal of medical systems Apr 3, 2024
The aim of the study is to evaluate and compare the quality and readability of responses generated by five different artificial intelligence (AI) chatbots-ChatGPT, Bard, Bing, Ernie, and Copilot-to the top searched queries of erectile dysfunction (ED...
Benchmarking Software Humans Artificial Intelligence Male Erectile Dysfunction Linguistics
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Benchmarking machine learning-based real-time respiratory signal predictors in 4D SBRT.

Medical physics Mar 27, 2024
BACKGROUND: Stereotactic body radiotherapy of thoracic and abdominal tumors has to account for respiratory intrafractional tumor motion. Commonly, an external breathing signal is continuously acquired that serves as a surrogate of the tumor motion an...
Radiosurgery Four-Dimensional Computed Tomography Benchmarking Machine Learning Respiration Humans Deep Learning Time Factors
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Integrated image and location analysis for wound classification: a deep learning approach.

Scientific reports Mar 25, 2024
The global burden of acute and chronic wounds presents a compelling case for enhancing wound classification methods, a vital step in diagnosing and determining optimal treatments. Recognizing this need, we introduce an innovative multi-modal network ...
Humans Neural Networks, Computer Deep Learning Benchmarking Accidental Injuries Neoplasms, Squamous Cell
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DANCE: a deep learning library and benchmark platform for single-cell analysis.

Genome biology Mar 19, 2024
DANCE is the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 po...
Deep Learning Single-Cell Analysis Gene Library Benchmarking Humans Algorithms
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DDFC: deep learning approach for deep feature extraction and classification of brain tumors using magnetic resonance imaging in E-healthcare system.

Scientific reports Mar 18, 2024
This research explores the use of gated recurrent units (GRUs) for automated brain tumor detection using MRI data. The GRU model captures sequential patterns and considers spatial information within individual MRI images and the temporal evolution of...
Benchmarking Radiopharmaceuticals Deep Learning Magnetic Resonance Imaging Brain Brain Neoplasms Humans
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