AIMC Topic: Female

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ASSESSMENT OF CENTRAL SEROUS CHORIORETINOPATHY DEPICTED ON COLOR FUNDUS PHOTOGRAPHS USING DEEP LEARNING.

Retina (Philadelphia, Pa.)
PURPOSE: To investigate whether and to what extent central serous chorioretinopathy (CSC) depicted on color fundus photographs can be assessed using deep learning technology.

Rapid Recalibration of Peri-Personal Space: Psychophysical, Electrophysiological, and Neural Network Modeling Evidence.

Cerebral cortex (New York, N.Y. : 1991)
Interactions between individuals and the environment occur within the peri-personal space (PPS). The encoding of this space plastically adapts to bodily constraints and stimuli features. However, these remapping effects have not been demonstrated on ...

Support vector machine prediction of obstructive sleep apnea in a large-scale Chinese clinical sample.

Sleep
STUDY OBJECTIVES: Polysomnography is the gold standard for diagnosis of obstructive sleep apnea (OSA) but it is costly and access is often limited. The aim of this study is to develop a clinically useful support vector machine (SVM)-based prediction ...

A deep learning-based automated diagnostic system for classifying mammographic lesions.

Medicine
BACKGROUND: Screening mammography has led to reduced breast cancer-specific mortality and is recommended worldwide. However, the resultant doctors' workload of reading mammographic scans needs to be addressed. Although computer-aided detection (CAD) ...

Detecting falls and estimation of daily habits with depth images using machine learning algorithms.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Different approaches have been proposed in the literature to detect the fall of an elderly person. In this paper, we propose a fall detection method based on the classification of parameters extracted from depth images. Three supervised learning meth...

Deep Learning Based Junctional Zone Quantification using 3D Transvaginal Ultrasound in Assisted Reproduction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The Uterine Junctional Zone (JZ) is identified as an important anatomical region in the implantation process during assisted reproduction. The JZ changes throughout the hormone stimulation cycle and has predictive value for implantation success. Desp...

Deep Learning based Quantification of Ovary and Follicles using 3D Transvaginal Ultrasound in Assisted Reproduction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Quantification of ovarian and follicular volume and follicle count are performed in clinical practice for diagnosis and management in assisted reproduction. Ovarian volume and Antral Follicle Count (AFC) are typically tracked over the ovulation cycle...

Wavelet Spectral Time-Frequency Training of Deep Convolutional Neural Networks for Accurate Identification of Micro-Scale Sharp Wave Biomarkers in the Post-Hypoxic-Ischemic EEG of Preterm Sheep.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Neonatal hypoxic-ischemic encephalopathy (HIE) evolves over different phases of time during recovery. Some neuroprotection treatments are only effective for specific, short windows of time during this evolution of injury. Clinically, we often do not ...

Deep Convolutional Neural Network and Reverse Biorthogonal Wavelet Scalograms for Automatic Identification of High Frequency Micro-Scale Spike Transients in the Post-Hypoxic-Ischemic EEG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Diagnosis of hypoxic-ischemic encephalopathy (HIE) is currently limited and prognostic biological markers are required for early identification of at risk infants at birth. Using pre-clinical data from our fetal sheep models, we have shown that micro...

Wavelet Spectral Deep-training of Convolutional Neural Networks for Accurate Identification of High-Frequency Micro-Scale Spike Transients in the Post-Hypoxic-Ischemic EEG of Preterm Sheep.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Early diagnosis and prognosis of babies with signs of hypoxic-ischemic encephalopathy (HIE) is currently limited and requires reliable prognostic biomarkers to identify at risk infants. Using our pre-clinical fetal sheep models, we have demonstrated ...