Studies of various characteristics of the human face indicate that it contains a wealth of information about health status. Most studies involve objective measurement of facial features as correlated with historical health information. But some indiv...
IEEE transactions on pattern analysis and machine intelligence
Apr 13, 2018
We present the largest database for visual kinship recognition, Families In the Wild (FIW), with over 13,000 family photos of 1,000 family trees with 4-to-38 members. It took only a small team to build FIW with efficient labeling tools and work-flow....
In this paper, we present a new automatic diagnosis method for facial acne vulgaris which is based on convolutional neural networks (CNNs). To overcome the shortcomings of previous methods which were the inability to classify enough types of acne vul...
PURPOSE: Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these...
OBJECTIVE: To develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment.
PURPOSE: To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs.
Computer methods and programs in biomedicine
Feb 22, 2018
BACKROUND AND OBJECTIVES: Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper presents an automat...
The Journal of investigative dermatology
Feb 8, 2018
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...
BACKGROUND: Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability.
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