Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda
Artificial intelligence can assist providers in a variety of patient care and intelligent health
systems. Artificial intelligence techniques ranging from machine learning to deep learning …
systems. Artificial intelligence techniques ranging from machine learning to deep learning …
[HTML][HTML] Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol
reporting by providing evidence-based recommendations for the minimum set of items to be …
reporting by providing evidence-based recommendations for the minimum set of items to be …
High-sensitivity high-resolution X-ray imaging with soft-sintered metal halide perovskites
To realize the potential of artificial intelligence in medical imaging, improvements in imaging
capabilities are required, as well as advances in computing power and algorithms. Hybrid …
capabilities are required, as well as advances in computing power and algorithms. Hybrid …
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
The CONSORT 2010 statement provides minimum guidelines for reporting randomised
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
[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 …
Learning to resize images for computer vision tasks
H Talebi, P Milanfar - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
For all the ways convolutional neural nets have revolutionized computer vision in recent
years, one important aspect has received surprisingly little attention: the effect of image size …
years, one important aspect has received surprisingly little attention: the effect of image size …
Comparing different deep learning architectures for classification of chest radiographs
Chest radiographs are among the most frequently acquired images in radiology and are
often the subject of computer vision research. However, most of the models used to classify …
often the subject of computer vision research. However, most of the models used to classify …
Impact of image resolution on deep learning performance in endoscopy image classification: An experimental study using a large dataset of endoscopic images
Recent trials have evaluated the efficacy of deep convolutional neural network (CNN)-based
AI systems to improve lesion detection and characterization in endoscopy. Impressive …
AI systems to improve lesion detection and characterization in endoscopy. Impressive …
YOLO-Fish: A robust fish detection model to detect fish in realistic underwater environment
Over the last few years, several research works have been performed to monitor fish in the
underwater environment aimed for marine research, understanding ocean geography, and …
underwater environment aimed for marine research, understanding ocean geography, and …
A merged molecular representation deep learning method for blood–brain barrier permeability prediction
The ability of a compound to permeate across the blood–brain barrier (BBB) is a significant
factor for central nervous system drug development. Thus, for speeding up the drug …
factor for central nervous system drug development. Thus, for speeding up the drug …