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Surveys

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

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Automatic classification of HEp-2 specimens by explainable deep learning and Jensen-Shannon reliability index.

The Anti-Nuclear Antibodies (ANA) test using Human Epithelial type 2 (HEp-2) cells in the Indirect I...

Pharmacists' perceptions of artificial intelligence: A national survey.

BACKGROUND: Artificial intelligence (AI) is a rapidly growing and evolving field impacting pharmacy ...

Public Perception on Artificial Intelligence-Driven Mental Health Interventions: Survey Research.

BACKGROUND: Artificial intelligence (AI) has become increasingly important in health care, generatin...

Mapping surface soil organic carbon density of cultivated land using machine learning in Zhengzhou.

Research on soil organic carbon (SOC) is crucial for improving soil carbon sinks and achieving the "...

Deep learning methods for 3D magnetic resonance image denoising, bias field and motion artifact correction: a comprehensive review.

Magnetic resonance imaging (MRI) provides detailed structural information of the internal body organ...

Keeping humans in the loop efficiently by generating question templates instead of questions using AI: Validity evidence on Hybrid AIG.

BACKGROUND: Manually creating multiple-choice questions (MCQ) is inefficient. Automatic item generat...

Concurrent validity and test reliability of the deep learning markerless motion capture system during the overhead squat.

Marker-based optical motion capture systems have been used as a cardinal vehicle to probe and unders...

Spatiotemporal Deep Learning-Based Cine Loop Quality Filter for Handheld Point-of-Care Echocardiography.

The reliability of automated image interpretation of point-of-care (POC) echocardiography scans depe...

Automatic 3-D Lamina Curve Extraction From Freehand 3-D Ultrasound Data Using Sequential Localization Recurrent Convolutional Networks.

Freehand 3-D ultrasound imaging is emerging as a promising modality for regular spine exams due to i...

The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale.

In recent years, a plethora of artificial intelligence (AI) chatbots have been developed and made av...

Audio-visual aesthetic teaching methods in college students' vocal music teaching by deep learning.

In recent times, characterized by the rapid advancement of science and technology, the educational s...

Developing novel spectral indices for precise estimation of soil pH and organic carbon with hyperspectral data and machine learning.

Accurate soil pH and soil organic carbon (SOC) estimations are vital for sustainable agriculture, as...

Advancing healthcare through mobile collaboration: a survey of intelligent nursing robots research.

Mobile collaborative intelligent nursing robots have gained significant attention in the healthcare ...

Integrating large language models in systematic reviews: a framework and case study using ROBINS-I for risk of bias assessment.

Large language models (LLMs) may facilitate and expedite systematic reviews, although the approach t...

A digital phenotyping dataset for impending panic symptoms: a prospective longitudinal study.

This study investigated the utilization of digital phenotypes and machine learning algorithms to pre...

Learning extreme expected shortfall and conditional tail moments with neural networks. Application to cryptocurrency data.

We propose a neural networks method to estimate extreme Expected Shortfall, and even more generally,...

Learning patterns of HIV-1 resistance to broadly neutralizing antibodies with reduced subtype bias using multi-task learning.

The ability to predict HIV-1 resistance to broadly neutralizing antibodies (bnAbs) will increase bnA...

Artificial intelligence in cytopathological applications for cancer: a review of accuracy and analytic validity.

BACKGROUND: Cytopathological examination serves as a tool for diagnosing solid tumors and hematologi...

Diminishing spectral bias in physics-informed neural networks using spatially-adaptive Fourier feature encoding.

Physics-informed neural networks (PINNs) have recently emerged as a promising framework for solving ...

Development of a survey-based stacked ensemble predictive model for autonomy preferences in patients with periodontal disease.

OBJECTIVES: This study aimed to develop a model to predict the autonomy preference (AP) and satisfac...

Generating and evaluating synthetic data in digital pathology through diffusion models.

Synthetic data is becoming a valuable tool for computational pathologists, aiding in tasks like data...

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