AIMC Topic: Humans

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Preface.

Biochimica et biophysica acta. Reviews on cancer

Layered deep learning for automatic mandibular segmentation in cone-beam computed tomography.

Journal of dentistry
OBJECTIVE: To develop and validate a layered deep learning algorithm which automatically creates three-dimensional (3D) surface models of the human mandible out of cone-beam computed tomography (CBCT) imaging.

Artificial Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by the Society of Radiographers AI working group.

Radiography (London, England : 1995)
INTRODUCTION: Artificial intelligence (AI) has started to be increasingly adopted in medical imaging and radiotherapy clinical practice, however research, education and partnerships have not really caught up yet to facilitate a safe and effective tra...

Deep Learning Algorithm Predicts Angiographic Coronary Artery Disease in Stable Patients Using Only a Standard 12-Lead Electrocardiogram.

The Canadian journal of cardiology
BACKGROUND: Current electrocardiogram analysis algorithms cannot predict the presence of coronary artery disease (CAD), especially in stable patients. This study assessed the ability of an artificial intelligence algorithm (ECGio; HEARTio Inc, Pittsb...

Assessment of Axillary Lymph Nodes for Metastasis on Ultrasound Using Artificial Intelligence.

Ultrasonic imaging
The purpose of this study was to evaluate an artificial intelligence (AI) system for the classification of axillary lymph nodes on ultrasound compared to radiologists. Ultrasound images of 317 axillary lymph nodes from patients referred for ultrasoun...

Surgical workflow recognition with 3DCNN for Sleeve Gastrectomy.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical workflow recognition is a crucial and challenging problem when building a computer-assisted surgery system. Current techniques focus on utilizing a convolutional neural network and a recurrent neural network (CNN-RNN) to solve the s...

Strategies for feature extraction from structural brain imaging in lesion-deficit modelling.

Human brain mapping
High-dimensional modelling of post-stroke deficits from structural brain imaging is highly relevant to basic cognitive neuroscience and bears the potential to be translationally used to guide individual rehabilitation measures. One strategy to optimi...

Dual scope method: A novel application of a simultaneous multi-image display system for a thoracoscopic robotic lobectomy.

Multimedia manual of cardiothoracic surgery : MMCTS
The advantages of a multi-input display system platform in robotic thoracic surgery have not been well described. We report the novel application of a multi-display system for simultaneous visualization of an additional thoracoscopic image during a r...

Generalized Deep Learning EEG Models for Cross-Participant and Cross-Task Detection of the Vigilance Decrement in Sustained Attention Tasks.

Sensors (Basel, Switzerland)
Tasks which require sustained attention over a lengthy period of time have been a focal point of cognitive fatigue research for decades, with these tasks including air traffic control, watchkeeping, baggage inspection, and many others. Recent researc...

Automated Flood Depth Estimates from Online Traffic Sign Images: Explorations of a Convolutional Neural Network-Based Method.

Sensors (Basel, Switzerland)
Flood depth monitoring is crucial for flood warning systems and damage control, especially in the event of an urban flood. Existing gauge station data and remote sensing data still has limited spatial and temporal resolution and coverage. Therefore, ...