AIMC Topic: Deep Learning

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Monkeypox Virus Detection and Deep Learning-based Approaches: Correspondence.

Journal of medical systems
This letter to the editor discusses the publication of a paper on monkeypox virus detection and deep learning-based approaches. Confounding issues regarding diagnosis are discussed.

Deep learning approach for prediction of exergy and emission parameters of commercial high by-pass turbofan engines.

Environmental science and pollution research international
Aviation emissions originated from the fuel burn have been hot topics by engineers and policy-makers due to their harmful effects on the environment and thereby human health as well as sustainability. In this study, it is tried that several emission ...

LiDAR and Deep Learning-Based Standing Tree Detection for Firebreaks Applications.

Sensors (Basel, Switzerland)
Forest fire prevention is very important for the protection of the ecological environment, which requires effective prevention and timely suppression. The opening of the firebreaks barrier contributes significantly to forest fire prevention. The deve...

Applying Deep Learning for Breast Cancer Detection in Radiology.

Current oncology (Toronto, Ont.)
Recent advances in deep learning have enhanced medical imaging research. Breast cancer is the most prevalent cancer among women, and many applications have been developed to improve its early detection. The purpose of this review is to examine how va...

Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases.

Scientific reports
Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-b...

Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image.

PloS one
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Imaging tests such as chest X-ray (CXR) and computed tomography (CT) can provide useful information to clinical staff for facilitating a diagnosi...

MR-self Noise2Noise: self-supervised deep learning-based image quality improvement of submillimeter resolution 3D MR images.

European radiology
OBJECTIVES: The study aimed to develop a deep neural network (DNN)-based noise reduction and image quality improvement by only using routine clinical scans and evaluate its performance in 3D high-resolution MRI.

Musculoskeletal radiologist-level performance by using deep learning for detection of scaphoid fractures on conventional multi-view radiographs of hand and wrist.

European radiology
OBJECTIVES: To assess how an artificial intelligence (AI) algorithm performs against five experienced musculoskeletal radiologists in diagnosing scaphoid fractures and whether it aids their diagnosis on conventional multi-view radiographs.