AIMC Topic: Humans

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Attend and Guide (AG-Net): A Keypoints-Driven Attention-Based Deep Network for Image Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This article presents a novel keypoints-based attention mechanism for visual recognition in still images. Deep Convolutional Neural Networks (CNNs) for recognizing images with distinctive classes have shown great success, but their performance in dis...

Artificial intelligence for the real world of breast screening.

European journal of radiology
Breast cancer screening with mammography reduces mortality in the women who attend by detecting high risk cancer early. It is far from perfect with variations in both sensitivity for the detection of cancer and very wide variations in specificity, le...

Mixed-data deep learning in repeated predictions of general medicine length of stay: a derivation study.

Internal and emergency medicine
The accurate prediction of likely discharges and estimates of length of stay (LOS) aid in effective hospital administration and help to prevent access block. Machine learning (ML) may be able to help with these tasks. For consecutive patients admitte...

Deep learning-based intravascular ultrasound segmentation for the assessment of coronary artery disease.

International journal of cardiology
BACKGROUND: Accurate segmentation of the coronary arteries with intravascular ultrasound (IVUS) is important to optimize coronary stent implantation. Recently, deep learning (DL) methods have been proposed to develop automatic IVUS segmentation. Howe...

Deep learning based segmentation of brain tissue from diffusion MRI.

NeuroImage
Segmentation of brain tissue types from diffusion MRI (dMRI) is an important task, required for quantification of brain microstructure and for improving tractography. Current dMRI segmentation is mostly based on anatomical MRI (e.g., T1- and T2-weigh...

Sparse deep neural networks on imaging genetics for schizophrenia case-control classification.

Human brain mapping
Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we ...

A deep learning based traffic crash severity prediction framework.

Accident; analysis and prevention
Highway work zones are most vulnerable roadway segments for congestion and traffic collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions at work zones is vital to reduce the response time for emergency unit...

Robotic D2 Total Gastrectomy with Fluorescent Lymphatic Mapping for Gastric Cancer: Effective Use of the 4th Arm.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Minimally invasive surgery techniques have evolved remarkably over the past few decades in the field of surgical oncology, including robotic techniques for gastric malignancies. Bedside surgical assistance is often limited by operating table space or...

Machine learning in asthma research: moving toward a more integrated approach.

Expert review of respiratory medicine
: Big data are reshaping the future of medicine. The growing availability and increasing complexity of data have favored the adoption of modern analytical and computational methodologies in every area of medicine. Over the past decades, asthma resear...