AIMC Topic: Humans

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Energy Expenditure Estimation of Tabata by Combining Acceleration and Heart Rate.

Frontiers in public health
Tabata training plays an important role in health promotion. Effective monitoring of exercise energy expenditure is an important basis for exercisers to adjust their physical activities to achieve exercise goals. The input of acceleration combined wi...

Specific IgE and IgG4 Profiles of House Dust Mite Components in Allergen-Specific Immunotherapy.

Frontiers in immunology
BACKGROUND: Allergen immunotherapy (AIT) can induce immune tolerance to allergens by activating multiple mechanisms, including promoting IgG4 synthesis and blunting IgE production. However, the longitudinal data of sIgE and sIgG4 to allergen componen...

Enabling CT-Scans for covid detection using transfer learning-based neural networks.

Journal of biomolecular structure & dynamics
Today, we are coping with the pandemic, and the novel virus is covertly evolving day by day. Therefore, a precautionary system to deal with the issue is required as early as possible. The last few years were very challenging for doctors, vaccine make...

Prediction of the axial lens position after cataract surgery using deep learning algorithms and multilinear regression.

Acta ophthalmologica
BACKGROUND: The prediction of anatomical axial intraocular lens position (ALP) is one of the major challenges in cataract surgery. The purpose of this study was to develop and test prediction algorithms for ALP based on deep learning strategies.

Singular Configuration Analysis and Singularity Avoidance with Application in an Intelligent Robotic Manipulator.

Sensors (Basel, Switzerland)
Recently, robotic sensor systems have gained more attention annually in complex system sense strategies. The robotic sensors sense the information from itself and the environment, and fuse information for the use of perception, decision, planning, an...

Development of Deep Learning-based Automatic Scan Range Setting Model for Lung Cancer Screening Low-dose CT Imaging.

Academic radiology
RATIONALE AND OBJECTIVES: To develop an automatic setting of a deep learning-based system for detecting low-dose computed tomography (CT) lung cancer screening scan range and compare its efficiency with the radiographer's performance.

Enzyme-Photocatalyst Tandem Microrobot Powered by Urea for Escherichia coli Biofilm Eradication.

Small (Weinheim an der Bergstrasse, Germany)
Urinary-based infections affect millions of people worldwide. Such bacterial infections are mainly caused by Escherichia coli (E. coli) biofilm formation in the bladder and/or urinary catheters. Herein, the authors present a hybrid enzyme/photocataly...

Linking Function and Structure with ReSensNet: Predicting Retinal Sensitivity from OCT using Deep Learning.

Ophthalmology. Retina
PURPOSE: The currently used measures of retinal function are limited by being subjective, nonlocalized, or taxing for patients. To address these limitations, we sought to develop and evaluate a deep learning (DL) method to automatically predict the f...

Deep Learning in the Management of Intracranial Aneurysms and Cerebrovascular Diseases: A Review of the Current Literature.

World neurosurgery
Intracranial aneurysms are a common asymptomatic vascular pathology, the rupture of which is a devastating event with a significant risk of morbidity and mortality. Aneurysm detection and risk stratification before rupture events are, therefore, impe...