Devices and Vaccines

Prediction of Prognosis in Patients with Trauma by Using Machine Learning.

We developed a machine learning algorithm to analyze trauma-related data and predict the mortality and chronic care needs of patients with trauma. We recruited admitted patients with trauma during 2015 and 2016 and collected their clinical data. Then, we subjected this database to different machine learning techniques and chose the one with the highest accuracy by using cross-validation. The pri...

Real-time driving risk assessment using deep learning with XGBoost.

Traffic crashes typically occur in a few seconds and real-time prediction can significantly benefit traffic safety management and the development of safety countermeasures. This paper presents a novel deep learning model for crash identification based on high-frequency, high-resolution continuous driving data. The method consists of feature engineering based on Convolutional Neural Network (CNN) a...

LidSonic V2.0: A LiDAR and Deep-Learning-Based Green Assistive Edge Device to Enhance Mobility for the Visually Impaired.

Over a billion people around the world are disabled, among whom 253 million are visually impaired or blind, and this number is greatly increasing due ...

Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.

OBJECTIVE: This study aimed to investigate whether a deep learning reconstruction (DLR) method improves the image quality, stent evaluation, and visib...

Comments on "Identifying psychological antecedents and predictors of vaccine hesitancy through machine learning: A cross sectional study among chronic disease patients of deprived urban neighbourhood, India".

Dear Editor, we read the publication by Rustagi et al. "Identifying psychological antecedents and predictors of vaccine hesitancy through machine lear...

Construction of a Basic Japanese Teaching Resource Base Based on a Deep Neural Network under a Big Data Environment.

A challenge for education and teaching in universities is posed by "Internet plus," which has made numerous educational resources at universities rich...

Machine-learning as a validated tool to characterize individual differences in free recall of naturalistic events.

The use of naturalistic stimuli, such as narrative movies, is gaining popularity in many fields, characterizing memory, affect, and decision-making. N...

Adverse events in the digital age and where to find them.

Exponential growth of health-related data collected by digital tools is a reality within pharmaceutical and medical device research and development. D...

Wireless Miniature Magnetic Phase-Change Soft Actuators.

Wireless miniature soft actuators are promising for various potential high-impact applications in medical, robotic grippers, and artificial muscles. H...

Lightweight On-Device Detection of Android Malware Based on the Koodous Platform and Machine Learning.

Currently, Android is the most popular operating system among mobile devices. However, as the number of devices with the Android operating system incr...

A Comprehensive Quantitative and Biological Neural Network Optimization Model of Sports Industry Structure Based on Knowledge Mapping.

In this paper, a comprehensive quantitative and biological neural network optimization model of sports industry structure is thoroughly studied and an...

Development of artificial intelligence model for supporting implant drilling protocol decision making.

Purpose This study aimed to develop an artificial intelligence (AI) model to support the determination of an appropriate implant drilling protocol usi...

Study on Accuracy Improvement of Slope Failure Region Detection Using Mask R-CNN with Augmentation Method.

We proposed an automatic detection method of slope failure regions using a semantic segmentation method called Mask R-CNN based on a deep learning alg...

Comparative studies of deep learning segmentation models for left ventricle segmentation.

One of the primary factors contributing to death across all age groups is cardiovascular disease. In the analysis of heart function, analyzing the lef...

Novel Internet of Things based approach toward diabetes prediction using deep learning models.

The integration of the Internet of Things with machine learning in different disciplines has benefited from recent technological advancements. In medi...

Integration of reference data from different Rapid-E devices supports automatic pollen detection in more locations.

Pollen is the most common cause of seasonal allergies, affecting over 33 % of the European population, even when considering only grasses. Informing t...

Ensemble latent assimilation with deep learning surrogate model: application to drop interaction in a microfluidics device.

A major challenge in the field of microfluidics is to predict and control drop interactions. This work develops an image-based data-driven model to fo...

Inter-Slice Resolution Improvement Using Convolutional Neural Network with Orbital Bone Edge-Aware in Facial CT Images.

The 3D modeling of orbital bones in facial CT images is essential to provide a customized implant for reconstructions of orbit and related structures ...

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This...

Evaluation of a hybrid pipeline for automated segmentation of solid lesions based on mathematical algorithms and deep learning.

We evaluate the accuracy of an original hybrid segmentation pipeline, combining variational and deep learning methods, in the segmentation of CT scans...