AIMC Topic: Reproducibility of Results

Clear Filters Showing 1841 to 1850 of 5908 articles

Reliably Filter Drug-Induced Liver Injury Literature With Natural Language Processing and Conformal Prediction.

IEEE journal of biomedical and health informatics
Drug-induced liver injury describes the adverse effects of drugs that damage the liver. Life-threatening results were also reported in severe cases. Therefore, liver toxicity is an important assessment for new drug candidates. These reports are docum...

Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces.

Nature communications
A wearable silent speech interface (SSI) is a promising platform that enables verbal communication without vocalization. The most widely studied methodology for SSI focuses on surface electromyography (sEMG). However, sEMG suffers from low scalabilit...

A robust prediction model for evaluation of plastic limit based on sieve # 200 passing material using gene expression programming.

PloS one
This study aims to propose a novel and high-accuracy prediction model of plastic limit (PL) based on soil particles passing through sieve # 200 (0.075 mm) using gene expression programming (GEP). PL is used for the classification of fine-grained soil...

Uncertainty Estimation Using Variational Mixture of Gaussians Capsule Network for Health Image Classification.

Computational intelligence and neuroscience
Capsule Networks have shown great promise in image recognition due to their ability to recognize the pose, texture, and deformation of objects and object parts. However, the majority of the existing capsule networks are deterministic with limited abi...

Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations.

The Science of the total environment
The latest Multi-angle Imaging Spectro Radiometer (MISR) Version (V) 23 aerosol optical depth (AOD) products were released, with an improved spatial resolution of 4.4 km, providing an unprecedented opportunity for the refined regional application. To...

Recent advances in applications of artificial intelligence in solid waste management: A review.

Chemosphere
Efficient management of solid waste is essential to lessen its potential health and environmental impacts. However, the current solid waste management practices encounter several challenges. The development of effective waste management systems using...

Visual body composition assessment methods: A 4-compartment model comparison of smartphone-based artificial intelligence for body composition estimation in healthy adults.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND & AIMS: Visual body composition (VBC) estimates produced from smartphone-based artificial intelligence represent a user-friendly and convenient way to automate body composition remotely and without the inherent geographical and monetary re...

Differentiating a pachychoroid and healthy choroid using an unsupervised machine learning approach.

Scientific reports
The purpose of this study was to introduce a new machine learning approach for differentiation of a pachychoroid from a healthy choroid based on enhanced depth-optical coherence tomography (EDI-OCT) imaging. This study included EDI-OCT images of 103 ...

Evaluation of Multimedia Courseware-Assisted Teaching Effect of Medical Images Based on the Deep Learning Algorithm.

Journal of environmental and public health
In order to improve the dynamic evaluation ability of medical image multimedia courseware-assisted teaching effect, the evaluation of medical image multimedia courseware-assisted teaching effect based on a deep learning algorithm is proposed. The sta...

Detecting High-Risk Factors and Early Diagnosis of Diabetes Using Machine Learning Methods.

Computational intelligence and neuroscience
Diabetes is a chronic disease that can cause several forms of chronic damage to the human body, including heart problems, kidney failure, depression, eye damage, and nerve damage. There are several risk factors involved in causing this disease, with ...