AIMC Topic: Deep Learning

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Monitoring the respiratory behavior of multiple cows based on computer vision and deep learning.

Journal of dairy science
Automatic respiration monitoring of dairy cows in modern farming not only helps to reduce manual labor but also increases the automation of health assessment. It is common for cows to congregate on farms, which poses a challenge for manual observatio...

Deep Learning-based Approach to Predict Pulmonary Function at Chest CT.

Radiology
Background Low-dose chest CT screening is recommended for smokers with the potential for lung function abnormality, but its role in predicting lung function remains unclear. Purpose To develop a deep learning algorithm to predict pulmonary function w...

Sooty Tern Optimization Algorithm-Based Deep Learning Model for Diagnosing NSCLC Tumours.

Sensors (Basel, Switzerland)
Lung cancer is one of the most common causes of cancer deaths in the modern world. Screening of lung nodules is essential for early recognition to facilitate treatment that improves the rate of patient rehabilitation. An increase in accuracy during l...

A multimodal deep learning model to infer cell-type-specific functional gene networks.

BMC bioinformatics
BACKGROUND: Functional gene networks (FGNs) capture functional relationships among genes that vary across tissues and cell types. Construction of cell-type-specific FGNs enables the understanding of cell-type-specific functional gene relationships an...

Deep learning method for risk identification of autonomous bus operation considering image data augmentation strategies.

Traffic injury prevention
OBJECTIVE: The autonomous bus is a key application scenario for autonomous driving technology. Identifying the risk of autonomous bus operation is of great significant to improve road traffic safety and promote the large-scale application of autonomo...

Standardized Fixation Zones and Cone Assessments for Revision Total Knee Arthroplasty Using Deep Learning.

The Journal of arthroplasty
BACKGROUND: Achieving adequate implant fixation is critical to optimize survivorship and postoperative outcomes after revision total knee arthroplasty (rTKA). Three anatomical zones (ie, epiphysis, metaphysis, and diaphysis) have been proposed to ass...

A Deep Learning Approach for Automated Bone Removal from Computed Tomography Angiography of the Brain.

Journal of digital imaging
Advanced visualization techniques such as maximum intensity projection (MIP) and volume rendering (VR) are useful for evaluating neurovascular anatomy on CT angiography (CTA) of the brain; however, interference from surrounding osseous anatomy is com...

Algorithmic encoding of protected characteristics in chest X-ray disease detection models.

EBioMedicine
BACKGROUND: It has been rightfully emphasized that the use of AI for clinical decision making could amplify health disparities. An algorithm may encode protected characteristics, and then use this information for making predictions due to undesirable...

How scan parameter choice affects deep learning-based coronary artery disease assessment from computed tomography.

Scientific reports
Recently, algorithms capable of assessing the severity of Coronary Artery Disease (CAD) in form of the Coronary Artery Disease-Reporting and Data System (CAD-RADS) grade from Coronary Computed Tomography Angiography (CCTA) scans using Deep Learning (...

Detection of acute promyelocytic leukemia in peripheral blood and bone marrow with annotation-free deep learning.

Scientific reports
While optical microscopy inspection of blood films and bone marrow aspirates by a hematologist is a crucial step in establishing diagnosis of acute leukemia, especially in low-resource settings where other diagnostic modalities are not available, the...