External validation of deep learning algorithms for radiologic diagnosis: a systematic review
Purpose To assess generalizability of published deep learning (DL) algorithms for radiologic
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
[HTML][HTML] Deep learning for chest X-ray analysis: A survey
E Çallı, E Sogancioglu, B van Ginneken… - Medical Image …, 2021 - Elsevier
Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …
image analysis tasks. As the most commonly performed radiological exam, chest …
[HTML][HTML] High-precision multiclass classification of lung disease through customized MobileNetV2 from chest X-ray images
In this study, multiple lung diseases are diagnosed with the help of the Neural Network
algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia …
algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia …
A scoping review of transfer learning research on medical image analysis using ImageNet
Objective Employing transfer learning (TL) with convolutional neural networks (CNNs), well-
trained on non-medical ImageNet dataset, has shown promising results for medical image …
trained on non-medical ImageNet dataset, has shown promising results for medical image …
xViTCOS: explainable vision transformer based COVID-19 screening using radiography
Objective: Since its outbreak, the rapid spread of COrona VIrus Disease 2019 (COVID-19)
across the globe has pushed the health care system in many countries to the verge of …
across the globe has pushed the health care system in many countries to the verge of …
AAPM task group report 273: recommendations on best practices for AI and machine learning for computer‐aided diagnosis in medical imaging
Rapid advances in artificial intelligence (AI) and machine learning, and specifically in deep
learning (DL) techniques, have enabled broad application of these methods in health care …
learning (DL) techniques, have enabled broad application of these methods in health care …
CXray-EffDet: chest disease detection and classification from X-ray images using the EfficientDet model
The competence of machine learning approaches to carry out clinical expertise tasks has
recently gained a lot of attention, particularly in the field of medical-imaging examination …
recently gained a lot of attention, particularly in the field of medical-imaging examination …
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
Shortly after deep learning algorithms were applied to Image Analysis, and more importantly
to medical imaging, their applications increased significantly to become a trend. Likewise …
to medical imaging, their applications increased significantly to become a trend. Likewise …
Clinical applications of artificial intelligence in radiology
C Mello-Thoms, CAB Mello - The British Journal of Radiology, 2023 - academic.oup.com
The rapid growth of medical imaging has placed increasing demands on radiologists. In this
scenario, artificial intelligence (AI) has become an attractive partner, one that may …
scenario, artificial intelligence (AI) has become an attractive partner, one that may …
The EMory BrEast imaging Dataset (EMBED): A racially diverse, granular dataset of 3.4 million screening and diagnostic mammographic images
JJ Jeong, BL Vey, A Bhimireddy, T Kim… - Radiology: Artificial …, 2023 - pubs.rsna.org
The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.4
Million Screening and Diagnostic Mammographic Images | Radiology: Artificial Intelligence …
Million Screening and Diagnostic Mammographic Images | Radiology: Artificial Intelligence …