AI Medical Compendium Journal:
Medical & biological engineering & computing

Showing 71 to 80 of 330 articles

PSFHSP-Net: an efficient lightweight network for identifying pubic symphysis-fetal head standard plane from intrapartum ultrasound images.

Medical & biological engineering & computing
The accurate selection of the ultrasound plane for the fetal head and pubic symphysis is critical for precisely measuring the angle of progression. The traditional method depends heavily on sonographers manually selecting the imaging plane. This proc...

FACNN: fuzzy-based adaptive convolution neural network for classifying COVID-19 in noisy CXR images.

Medical & biological engineering & computing
COVID-19 detection using chest X-rays (CXR) has evolved as a significant method for early diagnosis of the pandemic disease. Clinical trials and methods utilize X-ray images with computer and intelligent algorithms to improve detection and classifica...

Classification of exercise fatigue levels by multi-class SVM from ECG and HRV.

Medical & biological engineering & computing
Among the various physiological signals, electrocardiogram (ECG) is a valid criterion for the classification of various exercise fatigue. In this study, we combine features extracted by deep neural networks with linear features from ECG and heart rat...

Ensemble learning for retinal disease recognition under limited resources.

Medical & biological engineering & computing
Retinal optical coherence tomography (OCT) images provide crucial insights into the health of the posterior ocular segment. Therefore, the advancement of automated image analysis methods is imperative to equip clinicians and researchers with quantita...

BraNet: a mobil application for breast image classification based on deep learning algorithms.

Medical & biological engineering & computing
Mobile health apps are widely used for breast cancer detection using artificial intelligence algorithms, providing radiologists with second opinions and reducing false diagnoses. This study aims to develop an open-source mobile app named "BraNet" for...

Adversarial attacks and adversarial training for burn image segmentation based on deep learning.

Medical & biological engineering & computing
Deep learning has been widely applied in the fields of image classification and segmentation, while adversarial attacks can impact the model's results in image segmentation and classification. Especially in medical images, due to constraints from fac...

Subject-specific trunk segmental masses prediction for musculoskeletal models using artificial neural networks.

Medical & biological engineering & computing
Accurate determination of body segment parameters is crucial for studying human movement and joint forces using musculoskeletal (MSK) models. However, existing methods for predicting segment mass have limited generalizability and sensitivity to body ...

Recognition of diabetic retinopathy and macular edema using deep learning.

Medical & biological engineering & computing
Diabetic retinopathy (DR) and diabetic macular edema (DME) are both serious eye conditions associated with diabetes and if left untreated, and they can lead to permanent blindness. Traditional methods for screening these conditions rely on manual ima...

Neuroimage analysis using artificial intelligence approaches: a systematic review.

Medical & biological engineering & computing
In the contemporary era, artificial intelligence (AI) has undergone a transformative evolution, exerting a profound influence on neuroimaging data analysis. This development has significantly elevated our comprehension of intricate brain functions. T...

Uncertain prediction of deformable image registration on lung CT using multi-category features and supervised learning.

Medical & biological engineering & computing
The assessment of deformable registration uncertainty is an important task for the safety and reliability of registration methods in clinical applications. However, it is typically done by a manual and time-consuming procedure. We propose a novel aut...