AI Medical Compendium Journal:
Medicine

Showing 151 to 160 of 235 articles

The effects of robot-assisted left-hand training on hemispatial neglect in older patients with chronic stroke: A pilot and randomized controlled trial.

Medicine
BACKGROUND: Even though a variety of rehabilitative technique have been implemented to ameliorate neglect symptoms of patients with stoke, the effects of limb activation using a robotic device are still unknown. The purpose of this study was to inves...

Prediction of age and sex from paranasal sinus images using a deep learning network.

Medicine
This study was conducted to develop a convolutional neural network (CNN)-based model to predict the sex and age of patients by identifying unique unknown features from paranasal sinus (PNS) X-ray images.We employed a retrospective study design and us...

A machine-learning based approach to quantify fine crackles in the diagnosis of interstitial pneumonia: A proof-of-concept study.

Medicine
Fine crackles are frequently heard in patients with interstitial lung diseases (ILDs) and are known as the sensitive indicator for ILDs, although the objective method for analyzing respiratory sounds including fine crackles is not clinically availabl...

Effect of robot-assisted gait training on gait automaticity in Parkinson disease: A prospective, open-label, single-arm, pilot study.

Medicine
Gait automaticity is reduced in patients with Parkinson disease (PD) due to impaired habitual control. The aim of this study was to investigate the effect of robot-assisted gait training (RAGT) on gait automaticity as well as gait speed and balance i...

Automatic quality assessment for 2D fetal sonographic standard plane based on multitask learning.

Medicine
The quality control of fetal sonographic (FS) images is essential for the correct biometric measurements and fetal anomaly diagnosis. However, quality control requires professional sonographers to perform and is often labor-intensive. To solve this p...

Application of artificial intelligence in screening for adverse perinatal outcomes: A protocol for systematic review.

Medicine
The article presents a systematic review protocol. The aim of the study is an assessment of current studies regarding the application of artificial intelligence and neural networks in the screening for adverse perinatal outcomes. We intend to compare...

Adversarial attack on deep learning-based dermatoscopic image recognition systems: Risk of misdiagnosis due to undetectable image perturbations.

Medicine
Deep learning algorithms have shown excellent performances in the field of medical image recognition, and practical applications have been made in several medical domains. Little is known about the feasibility and impact of an undetectable adversaria...

Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.

Medicine
Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in health service research and may improve the prediction of health outcomes. The objective of this work...

Image quality improvement of single-shot turbo spin-echo magnetic resonance imaging of female pelvis using a convolutional neural network.

Medicine
We have developed a deep learning-based approach to improve image quality of single-shot turbo spin-echo (SSTSE) images of female pelvis. We aimed to compare the deep learning-based single-shot turbo spin-echo (DL-SSTSE) images of female pelvis with ...