Public Health & Policy

Work Force

Latest AI and machine learning research in work force for healthcare professionals.

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Training artificial neural networks using self-organizing migrating algorithm for skin segmentation.

This study presents an application of the self-organizing migrating algorithm (SOMA) to train artifi...

Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset.

Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable...

Effectiveness of data-augmentation on deep learning in evaluating rapid on-site cytopathology at endoscopic ultrasound-guided fine needle aspiration.

Rapid on-site cytopathology evaluation (ROSE) has been considered an effective method to increase th...

Generalizability assessment of AI models across hospitals in a low-middle and high income country.

The integration of artificial intelligence (AI) into healthcare systems within low-middle income cou...

HybMED: A Hybrid Neural Network Training Processor With Multi-Sparsity Exploitation for Internet of Medical Things.

Cloud-based training and edge-based inference modes for Artificial Intelligence of Medical Things (A...

CardioGuard: AI-driven ECG authentication hybrid neural network for predictive health monitoring in telehealth systems.

The increasing integration of telehealth systems underscores the importance of robust and secure met...

Semi-supervised recognition for artificial intelligence assisted pathology image diagnosis.

The analysis and interpretation of cytopathological images are crucial in modern medical diagnostics...

Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images.

BACKGROUND: Artificial intelligence (AI) in medical imaging diagnostics has huge potential, but huma...

Impact of artificial intelligence on the training of general surgeons of the future: a scoping review of the advances and challenges.

PURPOSE: To explore artificial intelligence's impact on surgical education, highlighting its advanta...

Interactive Surgical Training in Neuroendoscopy: Real-Time Anatomical Feature Localization Using Natural Language Expressions.

OBJECTIVE: This study addresses challenges in surgical education, particularly in neuroendoscopy, wh...

An Intersubject Brain-Computer Interface Based on Domain-Adversarial Training of Convolutional Neural Network.

OBJECTIVE: Attention decoding plays a vital role in daily life, where electroencephalography (EEG) h...

Efficacy of robot-assisted gait training on lower extremity function in subacute stroke patients: a systematic review and meta-analysis.

BACKGROUND: Robot-Assisted Gait Training (RAGT) is a novel technology widely employed in the field o...

Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study.

BACKGROUND: The aging population and the shortage of geriatric care workers are major global concern...

Teaching Motor Skills Without a Motor: A Semi-Passive Robot to Facilitate Learning.

Semi-passive rehabilitation robots resist and steer a patient's motion using only controllable passi...

Deep learning-enabled fluorescence imaging for surgical guidance: training for oral cancer depth quantification.

SIGNIFICANCE: Oral cancer surgery requires accurate margin delineation to balance complete resection...

Improving Human Activity Recognition With Wearable Sensors Through BEE: Leveraging Early Exit and Gradient Boosting.

Early-exiting has recently provided an ideal solution for accelerating activity inference by attachi...

Sensory Stimulation and Robot-Assisted Arm Training After Stroke: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Functional recovery after stroke is often limited, despite various treatment...

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