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Surveys

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

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A roadmap for improving data quality through standards for collaborative intelligence in human-robot applications.

Collaborative intelligence (CI) involves human-machine interactions and is deemed safety-critical be...

Dietary caffeine and its negative link to serum Klotho concentrations: evidence from the National Health and Nutrition Examination Survey.

BACKGROUND: This is the initial investigation assessing the association between caffeine consumption...

Deep Learning in Gene Regulatory Network Inference: A Survey.

Understanding the intricate regulatory relationships among genes is crucial for comprehending the de...

Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules With Desirable Properties.

In the past decade, Artificial Intelligence (AI) driven drug design and discovery has been a hot res...

Employing Machine Learning Techniques to Detect Protein Function: A Survey, Experimental, and Empirical Evaluations.

This review article delves deeply into the various machine learning (ML) methods and algorithms empl...

Evaluation of the clinical utility of lateral cephalometry reconstructed from computed tomography extracted by artificial intelligence.

This study assessed the accuracy and reliability of artificial intelligence (AI)-reconstructed image...

Integrating microbial profiling and machine learning for inference of drowning sites: a forensic investigation in the Northwest River.

Drowning incidents present significant challenges for forensic investigators in determining the exac...

Protein-protein interaction detection using deep learning: A survey, comparative analysis, and experimental evaluation.

This survey paper provides a comprehensive analysis of various Deep Learning (DL) techniques and alg...

Semi-supervised medical image segmentation network based on mutual learning.

BACKGROUND: Semi-supervised learning provides an effective means to address the challenge of insuffi...

Comparing statistical and deep learning approaches for simultaneous prediction of stand-level above- and belowground biomass in tropical forests.

Accurate and cost-effective prediction of aboveground biomass (AGB), belowground biomass (BGB), and ...

Word embedding for social sciences: an interdisciplinary survey.

Machine learning models learn low-dimensional representations from complex high-dimensional data. No...

Predictive utility of artificial intelligence on schizophrenia treatment outcomes: A systematic review and meta-analysis.

Identifying optimal treatment approaches for schizophrenia is challenging due to varying symptomatol...

Prediction of preterm birth using machine learning: a comprehensive analysis based on large-scale preschool children survey data in Shenzhen of China.

BACKGROUND: Preterm birth (PTB) is a significant cause of neonatal mortality and long-term health is...

Gender and Ethnicity Bias of Text-to-Image Generative Artificial Intelligence in Medical Imaging, Part 1: Preliminary Evaluation.

Generative artificial intelligence (AI) text-to-image production could reinforce or amplify gender a...

Deep learning versus human assessors: forensic sex estimation from three-dimensional computed tomography scans.

Cranial sex estimation often relies on visual assessments made by a forensic anthropologist followin...

A fact based analysis of decision trees for improving reliability in cloud computing.

The popularity of cloud computing (CC) has increased significantly in recent years due to its cost-e...

Gender bias in text-to-image generative artificial intelligence depiction of Australian paramedics and first responders.

INTRODUCTION: In Australia, almost 50 % of paramedics are female yet they remain under-represented i...

Prediction of Perceived Exertion Ratings in National Level Soccer Players Using Wearable Sensor Data and Machine Learning Techniques.

This study aimed to identify relationships between external and internal load parameters with subjec...

XGBoost as a reliable machine learning tool for predicting ancestry using autosomal STR profiles - Proof of method.

The aim of this study was to test the validity of a predictive model of ancestry affiliation based o...

Annotation Practices in Computational Pathology: A European Society of Digital and Integrative Pathology (ESDIP) Survey Study.

Integrating digital pathology and artificial intelligence (AI) algorithms can potentially improve di...

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