AIMC Topic: Humans

Clear Filters Showing 13511 to 13520 of 95995 articles

A radiopathomics model for predicting large-number cervical lymph node metastasis in clinical N0 papillary thyroid carcinoma.

European radiology
OBJECTIVES: This study aimed to develop a multimodal radiopathomics model utilising preoperative ultrasound (US) and fine-needle aspiration cytology (FNAC) to predict large-number cervical lymph node metastasis (CLNM) in patients with clinically lymp...

Machine learning web application for predicting varicose veins utilizing global prevalence data.

Phlebology
AimThis study aimed to develop a web-based machine learning (ML) model to predict the lifetime likelihood of developing varicose veins using global disease prevalence data.MethodsWe utilized data from a systematic review, registered under PROSPERO (C...

Machine-Learning Predictions of Cochlear Implant Functional Outcomes: A Systematic Review.

Ear and hearing
OBJECTIVES: Cochlear implant (CI) user functional outcomes are challenging to predict because of the variability in individual anatomy, neural health, CI device characteristics, and linguistic and listening experience. Machine learning (ML) technique...

Gesture recognition from surface electromyography signals based on the SE-DenseNet network.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: In recent years, significant progress has been made in the research of gesture recognition using surface electromyography (sEMG) signals based on machine learning and deep learning techniques. The main motivation for sEMG gesture recognit...

Generative artificial intelligence enables the generation of bone scintigraphy images and improves generalization of deep learning models in data-constrained environments.

European journal of nuclear medicine and molecular imaging
PURPOSE: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generat...

Deterministic Autoencoder using Wasserstein loss for tabular data generation.

Neural networks : the official journal of the International Neural Network Society
Tabular data generation is a complex task due to its distinctive characteristics and inherent complexities. While Variational Autoencoders have been adapted from the computer vision domain for tabular data synthesis, their reliance on non-determinist...

Artificial Intelligence in Fetal Growth Restriction Management: A Narrative Review.

Journal of clinical ultrasound : JCU
This narrative review examines the integration of Artificial Intelligence (AI) in prenatal care, particularly in managing pregnancies complicated by Fetal Growth Restriction (FGR). AI provides a transformative approach to diagnosing and monitoring FG...

Deep Learning-Assisted Computer-Aided Diagnosis System for Early Detection of Lung Cancer.

Journal of clinical ultrasound : JCU
PURPOSE: The largest cause of cancer-related fatalities worldwide is lung cancer. The dimensions and positioning of the primary tumor, the presence of lesions, the type of lung cancer like malignant or benign, and the good mental health diagnosis all...

Evaluation of navigation and robotic systems for percutaneous image-guided interventions: A novel metric for advanced imaging and artificial intelligence integration.

Diagnostic and interventional imaging
PURPOSE: Navigation and robotic systems aim to improve the accuracy and efficiency of percutaneous image-guided interventions, but the evaluation of their autonomy and integration of advanced imaging and artificial intelligence (AI) is lacking. The p...

Triaging mammography with artificial intelligence: an implementation study.

Breast cancer research and treatment
PURPOSE: Many breast centers are unable to provide immediate results at the time of screening mammography which results in delayed patient care. Implementing artificial intelligence (AI) could identify patients who may have breast cancer and accelera...