AIMC Topic: Benchmarking

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Revisiting Transfer Learning Method for Tuberculosis Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Transfer learning (TL) has been proven to be a good strategy for solving domain-specific problems in many deep learning (DL) applications. Typically, in TL, a pre-trained DL model is used as a feature extractor and the extracted features are then fed...
Problem Solving Machine Learning Benchmarking Neural Networks, Computer
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How to Determine If One Diagnostic Method, Such as an Artificial Intelligence Model, is Superior to Another: Beyond Performance Metrics.

Korean journal of radiology Jul 1, 2023
Humans Algorithms Benchmarking Neural Networks, Computer Artificial Intelligence
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Predicting Long-Term Type 2 Diabetes with Artificial Intelligence (AI): A Scoping Review.

Studies in health technology and informatics Jun 29, 2023
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder that affects a significant portion of the global population. Artificial intelligence (AI) has emerged as a promising tool for predicting T2DM risk. To provide an overview of the AI techn...
Machine Learning Diabetes Mellitus, Type 2 Humans Artificial Intelligence Benchmarking
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Optical Disc Segmentation from Retinal Fundus Images Using Deep Learning.

Studies in health technology and informatics Jun 29, 2023
The optical disc in the human retina can reveal important information about a person's health and well-being. We propose a deep learning-based approach to automatically identify the region in human retinal images that corresponds to the optical disc....
Benchmarking Humans Retina Fundus Oculi Deep Learning
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Artificial Intelligence in Breast Imaging: Challenges of Integration Into Clinical Practice.

Journal of breast imaging May 22, 2023
Artificial intelligence (AI) in breast imaging is a rapidly developing field with promising results. Despite the large number of recent publications in this field, unanswered questions have led to limited implementation of AI into daily clinical prac...
Diagnostic Imaging Benchmarking Radiologists Artificial Intelligence Humans Algorithms
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Recent application of artificial intelligence on histopathologic image-based prediction of gene mutation in solid cancers.

Briefings in bioinformatics May 19, 2023
PURPOSE: Evaluation of genetic mutations in cancers is important because distinct mutational profiles help determine individualized drug therapy. However, molecular analyses are not routinely performed in all cancers because they are expensive, time-...
Mutation Benchmarking Databases, Factual Thyroid Neoplasms Artificial Intelligence Humans
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Machine learning for RNA 2D structure prediction benchmarked on experimental data.

Briefings in bioinformatics May 19, 2023
Since the 1980s, dozens of computational methods have addressed the problem of predicting RNA secondary structure. Among them are those that follow standard optimization approaches and, more recently, machine learning (ML) algorithms. The former were...
Benchmarking RNA Algorithms Humans Machine Learning
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Towards an Explainable AI-Based Tool to Predict Preterm Birth.

Studies in health technology and informatics May 18, 2023
Preterm birth (PTB) is defined as delivery occurring before 37 weeks of gestation. In this paper, Artificial Intelligence (AI)-based predictive models are adapted to accurately estimate the probability of PTB. In doing so, pregnant women' objective r...
Machine Learning Algorithms Benchmarking Artificial Intelligence Humans Pregnancy Infant, Newborn Female Premature Birth
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Fairness in Artificial Intelligence: Regulatory Sanbox Evaluation of Bias Prevention for ECG Classification.

Studies in health technology and informatics May 18, 2023
As the use of artificial intelligence within healthcare is on the rise, an increased attention has been directed towards ethical considerations. Defining fairness in machine learning is a well explored topic with an extensive literature. However, suc...
Electrocardiography Bias Benchmarking Artificial Intelligence Machine Learning
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Benchmarking the Impact of Noise on Deep Learning-Based Classification of Atrial Fibrillation in 12-Lead ECG.

Studies in health technology and informatics May 18, 2023
Electrocardiography analysis is widely used in various clinical applications and Deep Learning models for classification tasks are currently in the focus of research. Due to their data-driven character, they bear the potential to handle signal noise ...
Humans Benchmarking Atrial Fibrillation Signal-To-Noise Ratio Algorithms Deep Learning Electrocardiography
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