Surveys

Reliability modelling of resting-state functional connectivity.

Resting-state functional magnetic resonance imaging (rs-fMRI) has an inherently low signal-to-noise ratio largely due to thermal and physiological noise that attenuates the functional connectivity (FC) estimates. Such attenuation limits the reliability of FC and may bias its association with other traits. Low reliability also limits heritability estimates. Classical test theory can be used to obta...

The Need for Ethnoracial Equity in Artificial Intelligence for Diabetes Management: Review and Recommendations.

There is clear evidence to suggest that diabetes does not affect all populations equally. Among adults living with diabetes, those from ethnoracial minority communities-foreign-born, immigrant, refugee, and culturally marginalized-are at increased risk of poor health outcomes. Artificial intelligence (AI) is actively being researched as a means of improving diabetes management and care; however, s...

Agreement in Risk of Bias Assessment Between RobotReviewer and Human Reviewers: An Evaluation Study on Randomised Controlled Trials in Nursing-Related Cochrane Reviews.

PURPOSE: RobotReviewer is a machine learning system for semi-automated assistance in risk of bias assessment. The tools's performance in randomized co...

Statistical foundation of Variational Bayes neural networks.

Despite the popularism of Bayesian neural networks (BNNs) in recent years, its use is somewhat limited in complex and big data situations due to the c...

Deep Learning for Multigrade Brain Tumor Classification in Smart Healthcare Systems: A Prospective Survey.

Brain tumor is one of the most dangerous cancers in people of all ages, and its grade recognition is a challenging problem for radiologists in health ...

A new health prediction model for a sensor network based on belief rule base with attribute reliability.

Health prediction plays an essential role in improving the reliability of a sensor network by guiding the network maintenance. However, affected by in...

Verifying explainability of a deep learning tissue classifier trained on RNA-seq data.

For complex machine learning (ML) algorithms to gain widespread acceptance in decision making, we must be able to identify the features driving the pr...

Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research.

By promising more accurate diagnostics and individual treatment recommendations, deep neural networks and in particular convolutional neural networks ...

Denoising non-steady state dynamic PET data using a feed-forward neural network.

The quality of reconstructed dynamic PET images, as well as the statistical reliability of the estimated pharmacokinetic parameters is often compromis...

Judges' evaluation reliability changes between identifiable and anonymous performance of hip-hop dance movements.

Hip-hop competitions are performed across the world. In the recent inclusion in the 2018 Youth Olympic Games, the assessment of hip-hop performance is...

Identifying Factors Associated with Neonatal Mortality in Sub-Saharan Africa using Machine Learning.

This study aimed at identifying the factors associated with neonatal mortality. We analyzed the Demographic and Health Survey (DHS) datasets from 10 S...

Prediction of Total Drug Clearance in Humans Using Animal Data: Proposal of a Multimodal Learning Method Based on Deep Learning.

Research into pharmacokinetics plays an important role in the development process of new drugs. Accurately predicting human pharmacokinetic parameters...

Co-designing diagnosis: Towards a responsible integration of Machine Learning decision-support systems in medical diagnostics.

RATIONALE: This paper aims to show how the focus on eradicating bias from Machine Learning decision-support systems in medical diagnosis diverts atten...

Validity and precision of the International Physical Activity Questionnaire for climacteric women using computational intelligence techniques.

This study aimed to evaluate the validity and precision of the International Physical Activity Questionnaire (IPAQ) for climacteric women using comput...

On-Device Reliability Assessment and Prediction of Missing Photoplethysmographic Data Using Deep Neural Networks.

Photoplethysmographic (PPG) measurements from ambulatory subjects may suffer from unreliability due to body movements and missing data segments due to...

Deep Neural Network Sleep Scoring Using Combined Motion and Heart Rate Variability Data.

Performance of wrist actigraphy in assessing sleep not only depends on the sensor technology of the actigraph hardware but also on the attributes of ...

Comparing the Ability of Regression Modeling and Bayesian Additive Regression Trees to Predict Costs in a Responsive Survey Design Context.

Responsive survey designs rely upon incoming data from the field data collection to optimize cost and quality tradeoffs. In order to make these decisi...

Data classification based on fractional order gradient descent with momentum for RBF neural network.

The weight-updating methods have played an important role in improving the performance of neural networks. To ameliorate the oscillating phenomenon in...

Machine Learning Techniques for Ophthalmic Data Processing: A Review.

Machine learning and especially deep learning techniques are dominating medical image and data analysis. This article reviews machine learning approac...

The influence of machine learning-based knowledge management model on enterprise organizational capability innovation and industrial development.

The aims are to explore the construction of the knowledge management model for engineering cost consulting enterprises, and to expand the application ...