Reporting standards for a Bland–Altman agreement analysis: A review of methodological reviews
O Gerke - Diagnostics, 2020 - mdpi.com
The Bland–Altman Limits of Agreement is a popular and widespread means of analyzing the
agreement of two methods, instruments, or raters in quantitative outcomes. An agreement …
agreement of two methods, instruments, or raters in quantitative outcomes. An agreement …
Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives
Therapies based on injecting living cells into patients offer a huge potential to cure many
degenerative and deadly diseases, with hundreds of clinical trials ongoing. Due to their …
degenerative and deadly diseases, with hundreds of clinical trials ongoing. Due to their …
Analyzing inter-reader variability affecting deep ensemble learning for COVID-19 detection in chest radiographs
Data-driven deep learning (DL) methods using convolutional neural networks (CNNs)
demonstrate promising performance in natural image computer vision tasks. However, their …
demonstrate promising performance in natural image computer vision tasks. However, their …
Creating clear and informative image-based figures for scientific publications
Scientists routinely use images to display data. Readers often examine figures first;
therefore, it is important that figures are accessible to a broad audience. Many resources …
therefore, it is important that figures are accessible to a broad audience. Many resources …
Why we need to report more than'Data were Analyzed by t-tests or ANOVA'
Transparent reporting is essential for the critical evaluation of studies. However, the
reporting of statistical methods for studies in the biomedical sciences is often limited. This …
reporting of statistical methods for studies in the biomedical sciences is often limited. This …
[HTML][HTML] Improved semantic segmentation of tuberculosis—consistent findings in chest x-rays using augmented training of modality-specific u-net models with weak …
Deep learning (DL) has drawn tremendous attention for object localization and recognition
in both natural and medical images. U-Net segmentation models have demonstrated …
in both natural and medical images. U-Net segmentation models have demonstrated …
Foundations of plasma standards
The field of low-temperature plasmas (LTPs) excels by virtue of its broad intellectual
diversity, interdisciplinarity and range of applications. This great diversity also challenges …
diversity, interdisciplinarity and range of applications. This great diversity also challenges …
One hertz versus ten hertz repetitive TMS treatment of PTSD: a randomized clinical trial
FA Kozel, K Van Trees, V Larson, S Phillips… - Psychiatry …, 2019 - Elsevier
The purpose of this trial was to test whether right prefrontal cortex 1 Hz versus 10 Hz rTMS
provides a significantly greater improvement in PTSD symptoms and/or function. Veterans …
provides a significantly greater improvement in PTSD symptoms and/or function. Veterans …
Detecting tuberculosis-consistent findings in lateral chest X-rays using an ensemble of CNNs and vision transformers
Research on detecting Tuberculosis (TB) findings on chest radiographs (or Chest X-rays:
CXR) using convolutional neural networks (CNNs) has demonstrated superior performance …
CXR) using convolutional neural networks (CNNs) has demonstrated superior performance …
Explanation and use of uncertainty quantified by Bayesian neural network classifiers for breast histopathology images
P Thiagarajan, P Khairnar… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Despite the promise of Convolutional neural network (CNN) based classification models for
histopathological images, it is infeasible to quantify its uncertainties. Moreover, CNNs may …
histopathological images, it is infeasible to quantify its uncertainties. Moreover, CNNs may …