Steep central island (SCI) formation after photorefractive keratectomy (PRK) and laser in situ keratomileusis (LASIK) represents a major drawback in the visual rehabilitation of patients after refractive laser surgery. Because of the small size of SCIs, current ablation algorithms are unable to properly calculate an ablation pattern for customized retreatment. We present the use of a new ablation algorithm for the treatment of SCIs that occurred after PRK or LASIK surgery. This algorithm uses a smaller zone of approximation and takes into account the spherical shift induced by removal of the SCI. In all 3 eyes treated, best spectacle-corrected visual acuity increased to 20/16 and remained stable at the 1- and 3-month follow-up, with disappearance of the SCI in corneal topography. This new treatment algorithm may be of benefit to patients experiencing visual side effects due to SCI formation after PRK or LASIK surgery.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jcrs.2006.02.008 | DOI Listing |
Sci Total Environ
January 2025
State Key Laboratory of Complex Nonferrous Metal Resources Clean Utilization, Kunming University of Science and Technology, Kunming, Yunnan 650093, PR China; Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650093, PR China. Electronic address:
Solid waste is one of the primary contributors to environmental pollution currently, it is crucial to enhance the prevention and control of solid waste pollution in environmental management. The effectiveness of the second stage of purification in the industrial zinc hydrometallurgy is determined by the concentration of cobalt ion. Manual testing and monitoring of cobalt ion concentration are time consuming and costly, and prone to delays, which can result in discharge of cobalt ion concentration that does not meet the standards, leading to water pollution.
View Article and Find Full Text PDFiScience
January 2025
Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, China.
To predict local progression after microwave ablation (MWA) in patients with stage I non-small cell lung cancer (NSCLC), we developed a CT-based radiomics model. Postoperative CT images were used. The intraclass correlation coefficients, two-sample t-test, least absolute shrinkage and selection operator (LASSO) regression, and Pearson correlation analysis were applied to select radiomics features and establish radiomics score.
View Article and Find Full Text PDFJ Food Sci
January 2025
College of Engineering, Jiangxi Agricultural University, Nanchang, China.
In the intelligent harvesting of eggplant, the lack of in situ identification technology makes it challenging to determine the maturity of purple eggplant fruit. The length of the fruit-setting date can determine when the eggplant is ready to be harvested. This study uses deep learning techniques to predict the date of fruit maturity.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
School of Information and Artificial Intelligence, Anhui Agricultural University, Changjiang West Road, Hefei, 230036, Anhui, China.
Drug-target interactions (DTIs) are pivotal in drug discovery and development, and their accurate identification can significantly expedite the process. Numerous DTI prediction methods have emerged, yet many fail to fully harness the feature information of drugs and targets or address the issue of feature redundancy. We aim to refine DTI prediction accuracy by eliminating redundant features and capitalizing on the node topological structure to enhance feature extraction.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai 519031, China.
Electroencephalogram (EEG) signals are important bioelectrical signals widely used in brain activity studies, cognitive mechanism research, and the diagnosis and treatment of neurological disorders. However, EEG signals are often influenced by various physiological artifacts, which can significantly affect data analysis and diagnosis. Recently, deep learning-based EEG denoising methods have exhibited unique advantages over traditional methods.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!