AIMC Topic: Humans

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Comparing blind spots of unsedated ultrafine, sedated, and unsedated conventional gastroscopy with and without artificial intelligence: a prospective, single-blind, 3-parallel-group, randomized, single-center trial.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: EGD is the most vital procedure for the diagnosis of upper GI lesions. We aimed to compare the performance of unsedated ultrathin transoral endoscopy (U-TOE), unsedated conventional EGD (C-EGD), and sedated C-EGD with or without ...

Human Gait Recognition Based on Frame-by-Frame Gait Energy Images and Convolutional Long Short-Term Memory.

International journal of neural systems
Human gait recognition is one of the most promising biometric technologies, especially for unobtrusive video surveillance and human identification from a distance. Aiming at improving recognition rate, in this paper we study gait recognition using de...

Deep Learning for Automated Classification of Inferior Vena Cava Filter Types on Radiographs.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To demonstrate the feasibility and evaluate the performance of a deep-learning convolutional neural network (CNN) classification model for automated identification of different types of inferior vena cava (IVC) filters on radiographs.

Machine Learning to Predict In-Hospital Morbidity and Mortality after Traumatic Brain Injury.

Journal of neurotrauma
Recently, successful predictions using machine learning (ML) algorithms have been reported in various fields. However, in traumatic brain injury (TBI) cohorts, few studies have examined modern ML algorithms. To develop a simple ML model for TBI outco...

Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images.

Medical image analysis
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow. The development of automated methods for nuclear segmentation and classification enables th...

Detection of Lung Cancer Lymph Node Metastases from Whole-Slide Histopathologic Images Using a Two-Step Deep Learning Approach.

The American journal of pathology
The application of deep learning for the detection of lymph node metastases on histologic slides has attracted worldwide attention due to its potentially important role in patient treatment and prognosis. Despite this attention, false-positive predic...

Automated Detection of Vulnerable Plaque for Intravascular Optical Coherence Tomography Images.

Cardiovascular engineering and technology
PURPOSE: Vulnerable plaque detection is important to acute coronary syndrome (ACS) diagnosis. In recent years, intravascular optical coherence tomography (IVOCT) imaging has been used for vulnerable plaque detection. Current automated detection metho...

Symmetry of generalized rivalry network models determines patterns of interocular grouping in four-location binocular rivalry.

Journal of neurophysiology
Previously, symmetry of network models has been proposed to account for interocular grouping during binocular rivalry. Here, we construct and analyze generalized rivalry network models with different types of symmetry (based on different kinds of exc...

Robotic direct reading device with spatial, temporal, and PID sensors for laboratory VOC exposure assessment.

Journal of occupational and environmental hygiene
This study evaluated a novel robotic direct reading method that used a real-time location system to measure the spatial-concentration distribution of volatile organic compounds (VOCs) in a chemistry laboratory. The CEMWIP II is a custom-made sensor t...