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Surveys

Latest AI and machine learning research in surveys for healthcare professionals.

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Artificial intelligence powered statistical genetics in biobanks.

Large-scale, sometimes nationwide, prospective genomic cohorts biobanking rich biological specimens ...

Reliability and accuracy of EEG interpretation for estimating age in preterm infants.

OBJECTIVES: To determine the accuracy of, and agreement among, EEG and aEEG readers' estimation of m...

On the use of machine learning algorithms in forensic anthropology.

The classification performance of the statistical methods binary logistic regression (BLR), multinom...

Improving the Reliability of Pharmacokinetic Parameters at Dynamic Contrast-enhanced MRI in Astrocytomas: A Deep Learning Approach.

Background Pharmacokinetic (PK) parameters obtained from dynamic contrast agent-enhanced (DCE) MRI e...

Test-Retest Reliability of Kinematic Assessments for Upper Limb Robotic Rehabilitation.

Robot-measured kinematic variables are increasingly used in neurorehabilitation to characterize moto...

Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges.

Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of pathological...

Deep learning in digital pathology image analysis: a survey.

Deep learning (DL) has achieved state-of-the-art performance in many digital pathology analysis task...

Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques.

Food consumption patterns have undergone changes that in recent years have resulted in serious healt...

Performance comparison of wavelet neural network and adaptive neuro-fuzzy inference system with small data sets.

In this work, performance of wavelet neural network (WNN) and adaptive neuro-fuzzy inference system ...

Reliability of the thumb localizing test and its validity against quantitative measures with a robotic device in patients with hemiparetic stroke.

OBJECTIVES: To examine the inter-rater reliability of the thumb localizing test (TLT) and its validi...

Use of AI-based tools for healthcare purposes: a survey study from consumers' perspectives.

BACKGROUND: Several studies highlight the effects of artificial intelligence (AI) systems on healthc...

Improved myocardial perfusion PET imaging using artificial neural networks.

Myocardial perfusion (MP) PET imaging plays a key role in risk assessment and stratification of pati...

Classification of Microarray Gene Expression Data Using an Infiltration Tactics Optimization (ITO) Algorithm.

A number of different feature selection and classification techniques have been proposed in literatu...

Efficient mapping of crash risk at intersections with connected vehicle data and deep learning models.

Traditional methods for identifying crash-prone roadways are mainly based on historical crash data. ...

Deploying Machine and Deep Learning Models for Efficient Data-Augmented Detection of COVID-19 Infections.

This generation faces existential threats because of the global assault of the novel Corona virus 20...

Prediction of remaining useful life (RUL) of Komatsu excavator under reliability analysis in the Weibull-frailty model.

It is an essential task to estimate the remaining useful life (RUL) of machinery in the mining secto...

A knowledge-based system to find over-the-counter medicines for self-medication.

This study developed a medicine query system based on Semantic Web and open data especially for self...

Ethical perceptions towards real-world use of companion robots with older people and people with dementia: survey opinions among younger adults.

BACKGROUND: Use of companion robots may reduce older people's depression, loneliness and agitation. ...

Use of artificial intelligence in diagnosis of head and neck precancerous and cancerous lesions: A systematic review.

This systematic review analyses and describes the application and diagnostic accuracy of Artificial ...

Investigating object compositionality in Generative Adversarial Networks.

Deep generative models seek to recover the process with which the observed data was generated. They ...

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