Surveys

A Systematic Review and Meta-Analysis of Pelvic Drain Insertion After Robot-Assisted Radical Prostatectomy.

To perform a systematic review and meta-analysis and to assess the clinical benefit of prophylactic...

Inherent Bias in Artificial Intelligence-Based Decision Support Systems for Healthcare.

The objective of this article is to discuss the inherent bias involved with artificial intelligence-...

Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children.

Autism has become a pressing healthcare challenge. The instruments used to aid diagnosis are time an...

A Survey on Deep Learning for Multimodal Data Fusion.

With the wide deployments of heterogeneous networks, huge amounts of data with characteristics of hi...

Modeling the Research Landscapes of Artificial Intelligence Applications in Diabetes (GAP).

The rising prevalence and global burden of diabetes fortify the need for more comprehensive and effe...

Identifying Lung Cancer Risk Factors in the Elderly Using Deep Neural Networks: Quantitative Analysis of Web-Based Survey Data.

BACKGROUND: Lung cancer is one of the most dangerous malignant tumors, with the fastest-growing morb...

Concurrent, face, content, and construct validity of the RobotiX Mentor simulator for robotic basic skills.

OBJECTIVES: To assess several criteria, such as concurrent, face, content, and construct validity of...

Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN).

The medical and machine learning communities are relying on the promise of artificial intelligence (...

Automated detection and classification of diabetes disease based on Bangladesh demographic and health survey data, 2011 using machine learning approach.

BACKGROUND AND AIMS: Diabetes has been recognized as a continuing health challenge for the twenty-fi...

HarborBot: A Chatbot for Social Needs Screening.

Accessing patients' social needs is a critical challenge at emergency departments (EDs). However, mo...

Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey when cities and towns are under quarantine.

We propose the use of a machine learning algorithm to improve possible COVID-19 case identification ...

Comparing machine and human reviewers to evaluate the risk of bias in randomized controlled trials.

BACKGROUND: Evidence from new health technologies is growing, along with demands for evidence to inf...

Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat with Radiofrequency Ultrasound Data Using One-dimensional Convolutional Neural Networks.

Background Radiofrequency ultrasound data from the liver contain rich information about liver micros...

Artificial neural networks for predicting social comparison effects among female Instagram users.

Systematic exposure to social media causes social comparisons, especially among women who compare th...

Common Audiological Functional Parameters (CAFPAs) for single patient cases: deriving statistical models from an expert-labelled data set.

Statistical knowledge about many patients could be exploited using machine learning to provide supp...

Assessing and Mitigating Bias in Medical Artificial Intelligence: The Effects of Race and Ethnicity on a Deep Learning Model for ECG Analysis.

BACKGROUND: Deep learning algorithms derived in homogeneous populations may be poorly generalizable ...

A Survey on Hand Pose Estimation with Wearable Sensors and Computer-Vision-Based Methods.

Real-time sensing and modeling of the human body, especially the hands, is an important research end...

Attitudes towards artificial intelligence within dermatology: an international online survey.

On the localness modeling for the self-attention based end-to-end speech synthesis.

Attention based end-to-end speech synthesis achieves better performance in both prosody and quality ...

Deep Learning in Physiological Signal Data: A Survey.

Deep Learning (DL), a successful promising approach for discriminative and generative tasks, has rec...

Machine learning and ligand binding predictions: A review of data, methods, and obstacles.

Computational predictions of ligand binding is a difficult problem, with more accurate methods being...