BACKGROUND: It is impossible to use the routine skeletal parts for gender identification if the skeleton of unknown human remains is obtained in a fragmented and incomplete state. The alternative is to use other parts of the skeleton for gender ident...
Due to growth in population, Individual persons with disabilities are increasing daily. To overcome the disability especially in Locked in State (LIS) due to Spinal Cord Injury (SCI), we planned to design four states moving robot from four imagery ta...
Today's life assistive devices were playing significant role in our life to communicate with others. In that modality Human Computer Interface (HCI) based Electrooculogram (EOG) playing vital part. By using this method we can able to overcome the con...
BACKGROUND: Male-to-female transgender patients desire to be identified, and treated, as female, in public and social settings. Facial feminization surgery entails a combination of highly visible changes in facial features. To study the effectiveness...
We studied the use of a rotating multi-layer 3D Light Detection And Ranging (LiDAR) sensor (specifically the Velodyne HDL-32E) mounted on a social robot for the estimation of features of people around the robot. While LiDARs are often used for robot ...
BACKGROUND: Studies of mammalian sexual dimorphism have traditionally involved the measurement of selected dimensions of particular skeletal elements and use of single data-analysis procedures. Consequently, such studies have been limited by a variet...
International journal of legal medicine
May 1, 2021
This paper introduces an automated method for estimating sex from the lower and upper limbs based on diaphyseal CSG properties. The proposed method was developed and evaluated using 389 femurs, 412 tibias, and 404 humeri of adult individuals from a m...
The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging studies. Confounders affect the relationship between input data (e.g., brain MRIs) and output variab...
We applied graph theory analysis on resting-state functional magnetic resonance imaging data to evaluate sex differences of brain functional topography in normal controls (NCs), early mild cognitive impairment (eMCI), and AD patients. These metrics w...
INTRODUCTION: This study was designed to develop and evaluate machine learning algorithms for predicting seizure due to acute tramadol poisoning, identifying high-risk patients and facilitating appropriate clinical decision-making.