AIMC Topic: Female

Clear Filters Showing 18121 to 18130 of 29210 articles

Facial Expressions Recognition for Human-Robot Interaction Using Deep Convolutional Neural Networks with Rectified Adam Optimizer.

Sensors (Basel, Switzerland)
The interaction between humans and an NAO robot using deep convolutional neural networks (CNN) is presented in this paper based on an innovative end-to-end pipeline method that applies two optimized CNNs, one for face recognition (FR) and another one...

Gait-Based Machine Learning for Classifying Patients with Different Types of Mild Cognitive Impairment.

Journal of medical systems
Mild cognitive impairment (MCI) may be caused by Alzheimer's disease, Parkinson's disease (PD), cerebrovascular accident, nutritional or metabolic disorders, or mental disorders. It is important to determine the cause and treatment of dementia as ear...

Machine learning volumetry of ischemic brain lesions on CT after thrombectomy-prospective diagnostic accuracy study in ischemic stroke patients.

Neuroradiology
PURPOSE: Ischemic lesion volume (ILV) is an important radiological predictor of functional outcome in patients with anterior circulation stroke. Our aim was to assess the agreement between automated ILV measurements on NCCT using the Brainomix softwa...

From a deep learning model back to the brain-Identifying regional predictors and their relation to aging.

Human brain mapping
We present a Deep Learning framework for the prediction of chronological age from structural magnetic resonance imaging scans. Previous findings associate increased brain age with neurodegenerative diseases and higher mortality rates. However, the im...

Age estimation using bloodstain miRNAs based on massive parallel sequencing and machine learning: A pilot study.

Forensic science international. Genetics
Age estimation is one of the most important components in the practice of forensic science, especially for body fluids or stains at crime scenes. Recent studies have focused on the application of DNA methylation for chronological age determination in...

Deep learning for mass detection in Full Field Digital Mammograms.

Computers in biology and medicine
In recent years, the use of Convolutional Neural Networks (CNNs) in medical imaging has shown improved performance in terms of mass detection and classification compared to current state-of-the-art methods. This paper proposes a fully automated frame...

Should We Ignore, Follow, or Biopsy? Impact of Artificial Intelligence Decision Support on Breast Ultrasound Lesion Assessment.

AJR. American journal of roentgenology
The objective of this study was to assess the impact of artificial intelligence (AI)-based decision support (DS) on breast ultrasound (US) lesion assessment. A multicenter retrospective review of 900 breast lesions (470/900 [52.2%] benign; 430/900 ...

Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.

NeuroImage. Clinical
Intrinsic connectivity networks (ICNs), including the default mode network (DMN), the central executive network (CEN), and the salience network (SN) have been shown to be aberrant in patients with posttraumatic stress disorder (PTSD). The purpose of ...

AI for reading screening mammograms: the need for circumspection.

European radiology
• The studies on AI reading of screening mammograms have methodological limitations that undermine the conclusion that AI could do better than radiologists. • These studies do not informon numbers of extra breast cancers found by AI that could repres...