Surgery

Surveys

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

5,794 articles
Stay Ahead - Weekly Surveys research updates
Subscribe
Browse Categories
Showing 1030-1050 of 5,794 articles
An empirical investigation of college students' acceptance of translation technologies.

With the advancement of information technology and artificial intelligence, translation technologies...

U-PASS: An uncertainty-guided deep learning pipeline for automated sleep staging.

With the increasing prevalence of machine learning in critical fields like healthcare, ensuring the ...

Performance of Fourier-based activation function in physics-informed neural networks for patient-specific cardiovascular flows.

BACKGROUND AND OBJECTIVES: Physics-informed neural networks (PINNs) can be used to inversely model c...

Robotic surgery: public perceptions and current misconceptions.

Whilst surgeons and robotic companies are key stakeholders involved in the adoption of robotic assis...

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer's disease.

Alzheimer's disease is one of the most important health-care challenges in the world. For decades, n...

Addressing bias in artificial intelligence for public health surveillance.

Components of artificial intelligence (AI) for analysing social big data, such as natural language p...

Machine Learning and Bias in Medical Imaging: Opportunities and Challenges.

Bias in health care has been well documented and results in disparate and worsened outcomes for at-r...

Combined substituent number utilized machine learning for the development of antimicrobial agent.

The utilization of machine learning has a potential to improve the environment of the development of...

Deep learning for head and neck semi-supervised semantic segmentation.

. Radiation therapy (RT) represents a prevalent therapeutic modality for head and neck (H&N) cancer....

Classification of self-limited epilepsy with centrotemporal spikes by classical machine learning and deep learning based on electroencephalogram data.

Electroencephalogram (EEG) has been widely utilized as a valuable assessment tool for diagnosing epi...

Application of the performance of machine learning techniques as support in the prediction of school dropout.

This article presents a study, intending to design a model with 90% reliability, which helps in the ...

Transformer Models in Healthcare: A Survey and Thematic Analysis of Potentials, Shortcomings and Risks.

Large Language Models (LLMs) such as General Pretrained Transformer (GPT) and Bidirectional Encoder ...

Graph Neural Network contextual embedding for Deep Learning on tabular data.

All industries are trying to leverage Artificial Intelligence (AI) based on their existing big data ...

Implications of Bias in Artificial Intelligence: Considerations for Cardiovascular Imaging.

PURPOSE OF REVIEW: Bias in artificial intelligence (AI) models can result in unintended consequences...

Fading memory as inductive bias in residual recurrent networks.

Residual connections have been proposed as an architecture-based inductive bias to mitigate the prob...

Deep reinforcement learning enables better bias control in benchmark for virtual screening.

Virtual screening (VS) has been incorporated into the paradigm of modern drug discovery. This field ...

Browse Categories