Surveys

Fast and powerful conditional randomization testing via distillation.

We consider the problem of conditional independence testing: given a response and covariates , we test the null hypothesis that . The conditional randomization test was recently proposed as a way to use distributional information about to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about . This flexibility, in princi...

The Optimal Machine Learning-Based Missing Data Imputation for the Cox Proportional Hazard Model.

An adequate imputation of missing data would significantly preserve the statistical power and avoid erroneous conclusions. In the era of big data, machine learning is a great tool to infer the missing values. The root means square error (RMSE) and the proportion of falsely classified entries (PFC) are two standard statistics to evaluate imputation accuracy. However, the Cox proportional hazards mo...

Graph matching survey for medical imaging: On the way to deep learning.

The interest on graph matching has not stopped growing since the late seventies. The basic idea of graph matching consists of generating graph represe...

Effects of different ozone treatments on the storage quality and stability of fresh peeled garlic.

In order to understand their impacts on the preservation of fresh garlic, varying concentrations of ozone gas and different storage temperatures were ...

Using distance on the Riemannian manifold to compare representations in brain and in models.

Representational similarity analysis (RSA) summarizes activity patterns for a set of experimental conditions into a matrix composed of pairwise compar...

The Use of Collections of Artificial Neural Networks to Improve the Control Quality of the Induction Soldering Process.

In industries that implement the technology of induction soldering, various sensors, including non-contact pyrometric ones, are widely used to control...

Deep learning of resting-state electroencephalogram signals for three-class classification of Alzheimer's disease, mild cognitive impairment and healthy ageing.

This study aimed to produce a novel deep learning (DL) model for the classification of subjects with Alzheimer's disease (AD), mild cognitive impairme...

A Soft Resistive Sensor with a Semicircular Cross-Sectional Channel for Soft Cardiac Catheter Ablation.

The field of soft robotics has attracted the interest of the medical community due to the ability of soft elastic materials to traverse the abnormal e...

A Novel Automatic Morphologic Analysis of Eyelids Based on Deep Learning Methods.

: To propose a deep-learning-based approach to automatically and objectively evaluate morphologic eyelid features using two-dimensional(2D) digital ph...

Semi-Supervised Anomaly Detection in Video-Surveillance Scenes in the Wild.

Surveillance cameras are being installed in many primary daily living places to maintain public safety. In this video-surveillance context, anomalies ...

UNRAQ-A Questionnaire for the Use of a Social Robot in Care for Older Persons. A Multi-Stakeholder Study and Psychometric Properties.

(1) Background: while there exist validated measures to assess the needs of older people, there are comparatively few validated tools to assess needs ...

Enhanced Diagnosis of Pneumothorax with an Improved Real-Time Augmentation for Imbalanced Chest X-rays Data Based on DCNN.

Pneumothorax is a common pulmonary disease that can lead to dyspnea and can be life-threatening. X-ray examination is the main means to diagnose this ...

Potential for optimizing the perioperative care in robotic prostatectomy patients by adoption of enhanced recovery after surgery principles.

Several benefits have been reported after applying the principles of enhanced recovery after surgery (ERAS) into the perioperative care of patients un...

Validity of robotic simulation for high-stakes examination: a pilot study.

Simulation is increasingly being used to train surgeons and access technical competency in robotic skills. The construct validity of using simulation ...

An artificial neural network-pharmacokinetic model and its interpretation using Shapley additive explanations.

We developed a method to apply artificial neural networks (ANNs) for predicting time-series pharmacokinetics (PKs), and an interpretable the ANN-PK mo...

Predicting youth diabetes risk using NHANES data and machine learning.

Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screeni...

Data-level Linkage of Multiple Surveys for Improved Understanding of Global Health Challenges.

Data-driven approaches can provide more enhanced insights for domain experts in addressing critical global health challenges, such as newborn and chil...

Design publicity of black box algorithms: a support to the epistemic and ethical justifications of medical AI systems.

In their article 'Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI', Durán and Jongsma discuss t...

Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data.

Transcriptomic atlases have improved our understanding of the correlations between gene-expression patterns and spatially varying properties of brain ...

Development of the Joint Commission of Taiwan's Smart Healthcare Standard.

It is well known that information technology (IT) can play a pivotal role in enhancing healthcare quality and patient safety. The use of computational...