Surveys

Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET.

Previous studies have demonstrated the feasibility of reducing noise with deep learning-based method...

Ethical and Legal Challenges of Artificial Intelligence in Nuclear Medicine.

Artificial intelligence (AI) in nuclear medicine has gained significant traction and promises to be ...

Improved Activity Recognition Combining Inertial Motion Sensors and Electroencephalogram Signals.

Human activity recognition and neural activity analysis are the basis for human computational neureo...

Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.

BACKGROUND: Early detection of melanoma can be lifesaving but this remains a challenge. Recent diagn...

Quantifying trunk neuromuscular control using seated balancing and stability threshold.

Performance during seated balancing is often used to assess trunk neuromuscular control, including e...

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by p...

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension.

The SPIRIT 2013 (The Standard Protocol Items: Recommendations for Interventional Trials) statement a...

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by p...

Disentangling time series between brain tissues improves fMRI data quality using a time-dependent deep neural network.

Functional MRI (fMRI) is a prominent imaging technique to probe brain function, however, a substanti...

A Time Series Data Filling Method Based on LSTM-Taking the Stem Moisture as an Example.

In order to solve the problem of data loss in sensor data collection, this paper took the stem moist...

Exploring gene-gene interaction in family-based data with an unsupervised machine learning method: EPISFA.

Gene-gene interaction (G × G) is thought to fill the gap between the estimated heritability of compl...

Bias and ethical considerations in machine learning and the automation of perioperative risk assessment.

Artificial Intelligence-Driven Oncology Clinical Decision Support System for Multidisciplinary Teams.

Watson for Oncology (WfO) is a clinical decision support system driven by artificial intelligence. I...

Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings.

BACKGROUND: Despite the vagueness and uncertainty that is intrinsic in any medical act, interpretati...

The FUTUREPAIN study: Validating a questionnaire to predict the probability of having chronic pain 7-10 years into the future.

OBJECTIVES: The FUTUREPAIN study develops a short general-purpose questionnaire, based on the biopsy...

Evidence-based medicine and machine learning: a partnership with a common purpose.

From its origins in epidemiology, evidence-based medicine has promulgated a rigorous approach to ass...

Machine learning in neurosurgery: a global survey.

BACKGROUND: Recent technological advances have led to the development and implementation of machine ...

A deep learning-based method for improving reliability of multicenter diffusion kurtosis imaging with varied acquisition protocols.

Multicenter magnetic resonance imaging is gaining more popularity in large-sample projects. Since bo...

There is No test-retest reliability of brain activation induced by robotic passive hand movement: A functional NIRS study.

INTRODUCTION: The basic paradigm of rehabilitation is based on the brain plasticity, and for promoti...

Evolution and impact of bias in human and machine learning algorithm interaction.

Traditionally, machine learning algorithms relied on reliable labels from experts to build predictio...

Role of Assistive Robots in the Care of Older People: Survey Study Among Medical and Nursing Students.

BACKGROUND: Populations are aging at an alarming rate in many countries around the world. There has ...