An artificial intelligence system for predicting mortality in COVID-19 patients using chest X-rays: a retrospective study
An Artificial Intelligence (AI) model based on CXRs and clinical parameters demonstrated high sensitivity and can be used as a ...
Validation of a Deep Learning Model to aid in COVID-19 Detection from Digital Chest Radiographs
Conclusion An Artificial Intelligence (AI) model based on CXRs and clinical parameters demonstrated high sensitivity and can be used ...
Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis
FIT compared 12 products and Deeptek AI solution is amongst the top 3 key solutions in the AI space which is redefining TB screening.
Elsevier - A new resource on AI powered computer automated detection software products for tuberculosis programmes...
DxTB by DeepTek has been identified as one of the eight CAD solutions worldwide, and one of the three CAD products available ...
Automatic Grading of Knee Osteoarthritis on the Kellgren-Lawrence Scale from Radiographs Using Convolutional ...
The severity of knee osteoarthritis is graded using the 5-point Kellgren-Lawrence (KL) scale where healthy knees are...
Automated chest radiograph diagnosis: A Twofer for Tuberculosis and COVID-19
TB is a pandemic which has challenged mankind for ages and Covid 19 is a recent onset fast-spreading pandemic.
Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentation
Deep learning semantic segmentation algorithms can localize abnormalities or opacities from chest radiographs.
Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical ...
The use of machine learning to develop intelligent software tools for the interpretation of radiology images has gained ...
Application of Federated Learning in Building a Robust COVID-19 Chest X-ray Classification Model
While developing artificial intelligence (AI)-based algorithms to solve problems, the amount of data plays a pivotal role - large amount ...
A Classical-Quantum Convolutional Neural Network for Detecting Pneumonia from Chest Radiographs
While many quantum computing techniques for machine learning have been proposed, their performance on real-world ...
Deep-learning-based automatic detection of pulmonary nodules from chest radiographs...
To assess a deep learning-based artificial intelligence model for the detection of pulmonary nodules on chest radiographs ...
Deep Learning Models for Calculation of Cardiothoracic Ratio from Chest Radiographs for Assisted ...
We propose an automated method based on deep learning to compute the cardiothoracic ratio and detect the presence...
Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentation
Deep learning semantic segmentation algorithms can localize abnormalities or opacities from chest radiographs..
An artificial intelligence system for predicting mortality in COVID-19 patients using chest X-rays: a retrospective study
An Artificial Intelligence (AI) model based on CXRs and clinical parameters demonstrated high sensitivity and can be used as a ...
Validation of a Deep Learning Model to aid in COVID-19 Detection from Digital Chest Radiographs
Conclusion An Artificial Intelligence (AI) model based on CXRs and clinical parameters demonstrated high sensitivity and can be used ...
Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentation
Deep learning semantic segmentation algorithms can localize abnormalities or opacities from chest radiographs..
Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical ...
The use of machine learning to develop intelligent software tools for the interpretation of radiology images has gained ...
Application of Federated Learning in Building a Robust COVID-19 Chest X-ray Classification Model
While developing artificial intelligence (AI)-based algorithms to solve problems, the amount of data plays a pivotal role - large amount ...
A Classical-Quantum Convolutional Neural Network for Detecting Pneumonia from Chest Radiographs
While many quantum computing techniques for machine learning have been proposed, their performance on real-world ...
Deep-learning-based automatic detection of pulmonary nodules from chest radiographs...
To assess a deep learning-based artificial intelligence model for the detection of pulmonary nodules on chest radiographs ...
Deep Learning Models for Calculation of Cardiothoracic Ratio from Chest Radiographs for Assisted ...
We propose an automated method based on deep learning to compute the cardiothoracic ratio and detect the presence...
Observer Performance Evaluation of the Feasibility of a Deep Learning Model to Detect Cardiomegaly on Chest Radiographs
This study introduces a deep learning (DL) model to automatically calculate the cardiothoracic ratio (CTR)
Validation of a Deep Learning Model for Detecting Chest Pathologies from Digital Chest Radiographs
This study introduces DxCOVID, a deep learning AI model by DeepTek trained to detect COVID-19 patterns on...
Comparison of Privacy-Preserving Distributed Deep Learning Methods in Healthcare
This study explores three AI techniques that train models to detect the disease on X-rays, all without sharing the actual images.
Automated Detection of COVID-19 from CT Scans Using Convolutional Neural Networks
In this study researchers built a model trained on both public and private Indian hospital data. Using the U-Net architecture, ...
Role of Edge Device and Cloud Machine Learning in Point-of-Care Solutions Using Imaging Diagnostics for Population Screening
This article by DeepTek reviews the role of edge devices and cloud machine learning as a solution for faster and efficient ...
Quantum Computing Methods for Supervised Learning
This research explores how quantum computing can be applied to solve "supervised learning problems,...
Vulnerability Due to Training Order in Split Learning
Split learning promises a solution by training models on divided data without sharing it directly. While secure...
Real-world analysis of artificial intelligence in musculoskeletal trauma
This review explores how deep learning, a recent AI advancement, has the potential to analyze medical images ...
Artificial intelligence in musculoskeletal radiology
This editorial explores the ability of AI to improve report quality, efficiency, and diagnostic accuracy by automating...