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Neural Networks in
Medical Imaging

J. Smith, A. Johnson, M. Williams

Abstract—

1. Introduction

[1]

2. Results

(t(30) = 1.5, p < 0.01)

Fig. 1

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Figure Reuse

Bioscience-scale automated detection of figure element reuse

This study presents an algorithm that detects figure element reuse in a large dataset of 760 thousand open access articles and 2 million figures, robust to various transformations. A panel review estimates that 0.6% of all articles contain fraudulent reuses, with inappropriate reuses occurring 43% across articles, 28% within an article, and 29% within a figure.

Missing Citation

Modeling citation worthiness by using attention-based bidirectional long short-term memory networks and interpretable models

This study develops an automated system using advanced neural networks to pinpoint sentences needing citations. It enhances document quality by identifying citation errors using a comprehensive dataset.

Figure Accessibility

A computational analysis of accessibility, readability, and explainability of figures in open access publications

This study develops computational techniques to assess the accessibility, readability, and explainability of figures in scientific publications. Our analysis reveals that approximately 20.6% of open access publications have issues related to these aspects, with detailed statistics provided for specific problems.

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Protect your science

–at any stage

Neural Networks in Medical Imaging

1. Introduction

2. Results

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