AIMC Topic: Benchmarking

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Medical Image Captioning Using Optimized Deep Learning Model.

Computational intelligence and neuroscience Mar 9, 2022
Medical image captioning provides the visual information of medical images in the form of natural language. It requires an efficient approach to understand and evaluate the similarity between visual and textual elements and to generate a sequence of ...
Biological Evolution Benchmarking Deep Learning Algorithms Language
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Active label cleaning for improved dataset quality under resource constraints.

Nature communications Mar 4, 2022
Imperfections in data annotation, known as label noise, are detrimental to the training of machine learning models and have a confounding effect on the assessment of model performance. Nevertheless, employing experts to remove label noise by fully re...
Diagnostic Imaging Benchmarking Delivery of Health Care Machine Learning Data Curation
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Radiomics and Artificial Intelligence: From Academia to Clinical Practice.

Radiology Mar 1, 2022
Artificial Intelligence Benchmarking Humans
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Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces.

Molecular informatics Feb 23, 2022
In this work, we benchmark a variety of single- and multi-task graph neural network (GNN) models against lower-bar and higher-bar traditional machine learning approaches employing human engineered molecular features. We consider four GNN variants - G...
Humans Neural Networks, Computer Benchmarking Machine Learning
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Domain Adaptation for Medical Image Analysis: A Survey.

IEEE transactions on bio-medical engineering Feb 18, 2022
Machine learning techniques used in computer-aided medical image analysis usually suffer from the domain shift problem caused by different distributions between source/reference data and target data. As a promising solution, domain adaptation has att...
Image Processing, Computer-Assisted Benchmarking Machine Learning
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TATL: Task agnostic transfer learning for skin attributes detection.

Medical image analysis Feb 13, 2022
Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network and then fine-tune on a medical target task. However, we argue that such approaches are suboptimal because medical datasets are largely different from I...
Neural Networks, Computer Machine Learning Humans Benchmarking Learning
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Qualitative Evaluation of Common Quantitative Metrics for Clinical Acceptance of Automatic Segmentation: a Case Study on Heart Contouring from CT Images by Deep Learning Algorithms.

Journal of digital imaging Jan 26, 2022
Organs-at-risk contouring is time consuming and labour intensive. Automation by deep learning algorithms would decrease the workload of radiotherapists and technicians considerably. However, the variety of metrics used for the evaluation of deep lear...
Algorithms Deep Learning Tomography, X-Ray Computed Humans Organs at Risk Benchmarking
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Mini-batch optimization enables training of ODE models on large-scale datasets.

Nature communications Jan 10, 2022
Quantitative dynamic models are widely used to study cellular signal processing. A critical step in modelling is the estimation of unknown model parameters from experimental data. As model sizes and datasets are steadily growing, established paramete...
Benchmarking Computational Biology Signal Transduction Cell Line, Tumor Models, Biological Gene Knockout Techniques Software Machine Learning Neoplasms Algorithms Humans
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Evolving kernel extreme learning machine for medical diagnosis via a disperse foraging sine cosine algorithm.

Computers in biology and medicine Dec 16, 2021
Kernel extreme learning machine (KELM) has been widely used in the fields of classification and identification since it was proposed. As the parameters in the KELM model have a crucial impact on performance, they must be optimized before the model ca...
Machine Learning Algorithms Benchmarking
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Review of automated performance metrics to assess surgical technical skills in robot-assisted laparoscopy.

Surgical endoscopy Nov 8, 2021
INTRODUCTION: Robot-assisted laparoscopy is a safe surgical approach with several studies suggesting correlations between complication rates and the surgeon's technical skills. Surgical skills are usually assessed by questionnaires completed by an ex...
Benchmarking Clinical Competence Humans Robotic Surgical Procedures Virtual Reality Laparoscopy Robotics
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