We reveal how implementing the homogeneous, multi-scale mapping frameworks observed in the mammalian brain's mapping systems radically improves the performance of a range of current robotic localization techniques. Roboticists have developed a range ...
This study examined and compared outcomes of deep learning (DL) in identifying swept-source optical coherence tomography (OCT) images without myopic macular lesions [i.e., no high myopia (nHM) vs. high myopia (HM)], and OCT images with myopic macular...
Assessing the well-being of an animal is hindered by the limitations of efficient communication between humans and animals. Instead of direct communication, a variety of parameters are employed to evaluate the well-being of an animal. Especially in t...
BACKGROUND: Nonophthalmologist physicians do not confidently perform direct ophthalmoscopy. The use of artificial intelligence to detect papilledema and other optic-disk abnormalities from fundus photographs has not been well studied.
Knee Osteoarthritis (OA) is a common musculoskeletal disorder in the United States. When diagnosed at early stages, lifestyle interventions such as exercise and weight loss can slow OA progression, but at later stages, only an invasive option is avai...
Accurate segmentation of brain tumors from magnetic resonance (MR) images play a pivot role in assisting diagnoses, treatments and postoperative evaluations. However, due to its structural complexities, e.g., fuzzy tumor boundaries with irregular sha...
Accurate segmentation of myocardial in cardiac MRI (magnetic resonance image) is key to effective rapid diagnosis and quantitative pathology analysis. However, a low-quality CMR (cardiac magnetic resonance) image with a large amount of noise makes it...
The widespread applications of high-throughput sequencing technology have produced a large number of publicly available gene expression datasets. However, due to the gene expression datasets have the characteristics of small sample size, high dimensi...
The Journal of investigative dermatology
Mar 31, 2020
Although deep learning algorithms have demonstrated expert-level performance, previous efforts were mostly binary classifications of limited disorders. We trained an algorithm with 220,680 images of 174 disorders and validated it using Edinburgh (1,3...