Surveys

A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data.

With the advances in technology and data science, machine learning (ML) is being rapidly adopted by ...

A deep learning approach to personality assessment: Generalizing across items and expanding the reach of survey-based research.

Traditional methods of personality assessment, and survey-based research in general, cannot make inf...

Artificial intelligence in medicine: A comprehensive survey of medical doctor's perspectives in Portugal.

Artificial Intelligence (AI) is increasingly influential across various sectors, including healthcar...

International survey on opinions and use of robot-assisted and laparoscopic minimally invasive pancreatic surgery: 5-year follow up.

BACKGROUND: Evidence on the value of minimally invasive pancreatic surgery (MIPS) has been increasin...

Prioritizing educational initiatives on emerging technologies for Italian pediatricians: bibliometric review and a survey.

BACKGROUND: Emerging technologies have demonstrated outstanding potential in improving healthcare, y...

Prediction and model evaluation for space-time data.

Evaluation metrics for prediction error, model selection and model averaging on space-time data are ...

Ethical Considerations and Fairness in the Use of Artificial Intelligence for Neuroradiology.

In this review, concepts of algorithmic bias and fairness are defined qualitatively and mathematical...

Automated estimation of mitral annular plane systolic excursion by artificial intelligence from 3D ultrasound recordings.

Perioperative monitoring of cardiac function is beneficial for early detection of cardiovascular com...

Fundus Image-Label Pairs Synthesis and Retinopathy Screening via GANs With Class-Imbalanced Semi-Supervised Learning.

Retinopathy is the primary cause of irreversible yet preventable blindness. Numerous deep-learning a...

Cycle-level traffic conflict prediction at signalized intersections with LiDAR data and Bayesian deep learning.

Real-time safety prediction models are vital in proactive road safety management strategies. This st...

Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset.

Preoperative radiological identification of mandibular canals is essential for maxillofacial surgery...

Robotic transcranial magnetic stimulation in the treatment of depression: a pilot study.

There has been an increasing demand for robotic coil positioning during repetitive transcranial magn...

Deep learning based correction of RF field induced inhomogeneities for T2w prostate imaging at 7 T.

At ultrahigh field strengths images of the body are hampered by B -field inhomogeneities. These pres...

Application of machine learning (individual vs stacking) models on MERRA-2 data to predict surface PM concentrations over India.

The spatial coverage of PM monitoring is non-uniform across India due to the limited number of groun...

A Case for Synthetic Data in Regulatory Decision-Making in Europe.

Regulators are faced with many challenges surrounding health data usage, including privacy, fragment...

Norwegian radiologists' expectations of artificial intelligence in mammographic screening - A cross-sectional survey.

PURPOSE: To explore Norwegian breast radiologists' expectations of adding artificial intelligence (A...

Robotic Medtronic Hugo™ RAS System Is Now Reality: Introduction to a New Simulation Platform for Training Residents.

The use of robotic surgery (RS) in urology has grown exponentially in the last decade, but RS traini...

Editorial Comment to Evaluation of sexual function after robot-assisted radical prostatectomy: A farewell to IIEF questionnaire.

Individual-Level Prediction of Exposure Therapy Outcome Using Structural and Functional MRI Data in Spider Phobia: A Machine-Learning Study.

Machine-learning prediction studies have shown potential to inform treatment stratification, but rec...

Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators.

The class of doubly robust (DR) functionals studied by Rotnitzky et al. (2021) is of central importa...

Machine learning with multimodal neuroimaging data to classify stages of Alzheimer's disease: a systematic review and meta-analysis.

In recent years, Alzheimer's disease (AD) has been a serious threat to human health. Researchers and...