Artificial intelligence in the anterior segment of eye diseases

Ophthalmology is a subject that highly depends on imaging examination.Artificial intelligence(AI)technology has great potential in medical imaging analysis,including image diagnosis,classification,grading,guiding treatment and evaluating prognosis.The combination of the two can realize mass screening of grass-roots eye health,making it possible to seek medical treatment in the mode of“first treatment at the grass-roots level,two-way referral,emergency and slow treatment,and linkage between the upper and lower levels”.On the basis of summarizing the AI technology carried out by scholars and their teams all over the world in the field of ophthalmology,quite a lot of studies have confirmed that machine learning can assist in diagnosis,grading,providing optimal treatment plans and evaluating prognosis in corneal and conjunctival diseases,ametropia,lens diseases,glaucoma,iris diseases,etc.This paper systematically shows the application and progress of AI technology in common anterior segment ocular diseases,the current limitations,and prospects for the future.

Endurable SSD-Based Read Cache for Improving the Performance of Selective Restore from Deduplication Systems

Deduplication has been commonly used in both enterprise storage systems and cloud storage. To overcome the performance challenge for the selective restore operations of deduplication systems, solid-state-drive-based （i.e., SSD-based） re^d cache cm, be deployed for speeding up by caching popular restore contents dynamically. Unfortunately, frequent data updates induced by classical cache schemes （e.g., LRU and LFU） significantly shorten SSDs＇ lifetime while slowing down I/O processes in SSDs. To address this problem, we propose a new solution -- LOP-Cache to greatly improve tile write durability of SSDs as well as I/O performance by enlarging the proportion of long-term popular （LOP） data among data written into SSD-based cache. LOP-Cache keeps LOP data in the SSD cache for a long time period to decrease the number of cache replacements. Furthermore, it prevents unpopular or unnecessary data in deduplication containers from being written into the SSD cache. We implemented LOP-Cache in a prototype deduplication system to evaluate its pertbrmance. Our experimental results indicate that LOP-Cache shortens the latency of selective restore by an average of 37.3% at the cost of a small SSD-based cache with only 5.56% capacity of the deduplicated data. Importantly, LOP-Cache improves SSDs＇ lifetime by a factor of 9.77. The evidence shows that LOP-Cache offers a cost-efficient SSD-based read cache solution to boost performance of selective restore for deduplication systems.