BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning

With the surge of large-scale pre-trained models (PTMs), fine-tuning these models to numerous downstream tasks becomes a crucial problem. Consequently, parameter efficient transfer learning (PETL) of large models has grasped huge attention. While recent PETL methods showcase impressive performance, they rely on optimistic assumptions: 1) the entire parameter set of a PTM is available, and 2) a sufficiently large memory capacity for the fine-tuning is equipped. However, in most real-world applications, PTMs are served as a black-box API or proprietary software without explicit parameter accessibility. Besides, it is hard to meet a large memory requirement for modern PTMs. In this work, we propose black-box visual prompting (BlackVIP), which efficiently adapts the PTMs without knowledge about model architectures and parameters. BlackVIP has two components; 1) Coordinator and 2) simultaneous perturbation stochastic approximation with gradient correction (SPSA-GC). The Coordinator designs input-dependent image-shaped visual prompts, which improves few-shot adaptation and robustness on distribution/location shift. SPSA-GC efficiently estimates the gradient of a target model to update Coordinator. Extensive experiments on 16 datasets demonstrate that BlackVIP enables robust adaptation to diverse domains without accessing PTMs' parameters, with minimal memory requirements. Code: \url{https://github.com/changdaeoh/BlackVIP}Comment: Accepted to CVPR 202

Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores

Aims: This study aims to evaluate the ability of a deep-learning-based cardiovascular disease (CVD) retinal biomarker, Reti-CVD, to identify individuals with intermediate- and high-risk for CVD. Methods and results: We defined the intermediate- and high-risk groups according to Pooled Cohort Equation (PCE), QRISK3, and modified Framingham Risk Score (FRS). Reti-CVD’s prediction was compared to the number of individuals identified as intermediate- and high-risk according to standard CVD risk assessment tools, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the results. In the UK Biobank, among 48 260 participants, 20 643 (42.8%) and 7192 (14.9%) were classified into the intermediate- and high-risk groups according to PCE, and QRISK3, respectively. In the Singapore Epidemiology of Eye Diseases study, among 6810 participants, 3799 (55.8%) were classified as intermediate- and high-risk group according to modified FRS. Reti-CVD identified PCE-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.7%, 87.6%, 86.5%, and 84.0%, respectively. Reti-CVD identified QRISK3-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.6%, 85.5%, 49.9%, and 96.6%, respectively. Reti-CVD identified intermediate- and high-risk groups according to the modified FRS with a sensitivity, specificity, PPV, and NPV of 82.1%, 80.6%, 76.4%, and 85.5%, respectively. Conclusion: The retinal photograph biomarker (Reti-CVD) was able to identify individuals with intermediate and high-risk for CVD, in accordance with existing risk assessment tools

Atmospheric-Pressure Plasma Jet Induces Apoptosis Involving Mitochondria via Generation of Free Radicals

The plasma jet has been proposed as a novel therapeutic method for anticancer treatment. However, its biological effects and mechanism of action remain elusive. Here, we investigated its cell death effects and underlying molecular mechanisms, using air and N2 plasma jets from a micro nozzle array. Treatment with air or N2 plasma jets caused apoptotic death in human cervical cancer HeLa cells, simultaneously with depolarization of mitochondrial membrane potential. In addition, the plasma jets were able to generate reactive oxygen species (ROS), which function as surrogate apoptotic signals by targeting the mitochondrial membrane potential. Antioxidants or caspase inhibitors ameliorated the apoptotic cell death induced by the air and N2 plasma jets, suggesting that the plasma jet may generate ROS as a proapoptotic cue, thus initiating mitochondria-mediated apoptosis. Taken together, our data suggest the potential employment of plasma jets as a novel therapy for cancer

Comparison of Higher-Order Aberration and Contrast Sensitivity in Monofocal and Multifocal Intraocular Lenses

PURPOSE: The visual performance of pseudophakic eyes depends on the type of intraocular lenses (IOLs) that are implanted. Aspherical and multifocal IOLs have recently been developed to improve visual quality after cataract surgery, but multifocal IOLs can be associated with decreased contrast sensitivity (CS), halos, and glare. This study compares the visual performance of monofocal and multifocal IOLs by measurement of higher-order aberrations (HOAs) and CS values. MATERIALS AND METHODS: HOAs and CS values of 42 eyes with implanted monofocal IOLs and 40 eyes with implanted multifocal IOLs were measured preoperatively and more than 6 months after surgery. In the multifocal IOL group, HOAs and CS values were also measured with addition of a trial lens of -0.5 diopter (D) to evaluate the compensatory effect on spherical aberration. RESULTS: CS values of the multifocal IOL group were significantly lower than those of the monofocal IOL group for all spatial frequencies tested (p<0.01), and the spherical aberration was significantly higher in the multifocal IOL group than in the monofocal IOL group (p<0.001). Addition of a -0.5 D lens to the multifocal IOL group decreased the difference in CS between the two groups (p=0.003). CONCLUSION: Increased spherical aberration may contribute to lower CS in the multifocal IOL group. In such cases, CS can be improved by addition of a -0.5 D lens to compensate for the spherical aberration.ope

Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores.

AimsThis study aims to evaluate the ability of a deep-learning-based cardiovascular disease (CVD) retinal biomarker, Reti-CVD, to identify individuals with intermediate- and high-risk for CVD.Methods and resultsWe defined the intermediate- and high-risk groups according to Pooled Cohort Equation (PCE), QRISK3, and modified Framingham Risk Score (FRS). Reti-CVD's prediction was compared to the number of individuals identified as intermediate- and high-risk according to standard CVD risk assessment tools, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the results. In the UK Biobank, among 48 260 participants, 20 643 (42.8%) and 7192 (14.9%) were classified into the intermediate- and high-risk groups according to PCE, and QRISK3, respectively. In the Singapore Epidemiology of Eye Diseases study, among 6810 participants, 3799 (55.8%) were classified as intermediate- and high-risk group according to modified FRS. Reti-CVD identified PCE-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.7%, 87.6%, 86.5%, and 84.0%, respectively. Reti-CVD identified QRISK3-based intermediate- and high-risk groups with a sensitivity, specificity, PPV, and NPV of 82.6%, 85.5%, 49.9%, and 96.6%, respectively. Reti-CVD identified intermediate- and high-risk groups according to the modified FRS with a sensitivity, specificity, PPV, and NPV of 82.1%, 80.6%, 76.4%, and 85.5%, respectively.ConclusionThe retinal photograph biomarker (Reti-CVD) was able to identify individuals with intermediate and high-risk for CVD, in accordance with existing risk assessment tools

Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank

BackgroundCurrently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical intervention. However, this benchmark has limited efficacy in clinical practice and the need for a more simple, non-invasive risk stratification tool is necessary. Retinal photography is becoming increasingly acceptable as a non-invasive imaging tool for CVD. Previously, we developed a novel CVD risk stratification system based on retinal photographs predicting future CVD risk. This study aims to further validate our biomarker, Reti-CVD, (1) to detect risk group of ≥ 10% in 10-year CVD risk and (2) enhance risk assessment in individuals with QRISK3 of 7.5-10% (termed as borderline-QRISK3 group) using the UK Biobank.MethodsReti-CVD scores were calculated and stratified into three risk groups based on optimized cut-off values from the UK Biobank. We used Cox proportional-hazards models to evaluate the ability of Reti-CVD to predict CVD events in the general population. C-statistics was used to assess the prognostic value of adding Reti-CVD to QRISK3 in borderline-QRISK3 group and three vulnerable subgroups.ResultsAmong 48,260 participants with no history of CVD, 6.3% had CVD events during the 11-year follow-up. Reti-CVD was associated with an increased risk of CVD (adjusted hazard ratio [HR] 1.41; 95% confidence interval [CI], 1.30-1.52) with a 13.1% (95% CI, 11.7-14.6%) 10-year CVD risk in Reti-CVD-high-risk group. The 10-year CVD risk of the borderline-QRISK3 group was greater than 10% in Reti-CVD-high-risk group (11.5% in non-statin cohort [n = 45,473], 11.5% in stage 1 hypertension cohort [n = 11,966], and 14.2% in middle-aged cohort [n = 38,941]). C statistics increased by 0.014 (0.010-0.017) in non-statin cohort, 0.013 (0.007-0.019) in stage 1 hypertension cohort, and 0.023 (0.018-0.029) in middle-aged cohort for CVD event prediction after adding Reti-CVD to QRISK3.ConclusionsReti-CVD has the potential to identify individuals with ≥ 10% 10-year CVD risk who are likely to benefit from earlier preventative CVD interventions. For borderline-QRISK3 individuals with 10-year CVD risk between 7.5 and 10%, Reti-CVD could be used as a risk enhancer tool to help improve discernment accuracy, especially in adult groups that may be pre-disposed to CVD

Investigation of SiO2 Etch Characteristics by C6F6/Ar/O2 Plasmas Generated Using Inductively Coupled Plasma and Capacitively Coupled Plasma

The etching properties of C6F6/Ar/O2 in both an inductively coupled plasma (ICP) system and a capacitively coupled plasma (CCP) system were evaluated to investigate the effects of high C/F ratio of perfluorocarbon (PFC) gas on the etch characteristics of SiO2. When the SiO2 masked with ACL was etched with C6F6, for the CCP system, even though the etch selectivity was very high (20 ~ infinite), due to the heavy-ion bombardment possibly caused by the less dissociated high-mass ions from C6F6, tapered SiO2 etch profiles were observed. In the case of the ICP system, due to the higher dissociation of C6F6 and O2 compared to the CCP system, the etching of SiO2 required a much lower ratio of O2/C6F6 (~1.0) while showing a higher maximum SiO2 etch rate (~400 nm/min) and a lower etch selectivity (~6.5) compared with the CCP system. For the ICP etching, even though the etch selectivity was much lower than that by the CCP etching, due to less heavy-mass-ion bombardment in addition to an adequate fluorocarbon layer formation on the substrate caused by heavily dissociated species, highly anisotropic SiO2 etch profiles could be obtained at the optimized condition of the O2/C6F6 ratio (~1.0)

Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma

Purpose: To analyze the efficacy of a deep learning (DL)-based artificial intelligence (AI)-based algorithm in detecting the presence of diabetic retinopathy (DR) and glaucoma suspect as compared to the diagnosis by specialists secondarily to explore whether the use of this algorithm can reduce the cross-referral in three clinical settings: a diabetologist clinic, retina clinic, and glaucoma clinic. Methods: This is a prospective observational study. Patients between 35 and 65 years of age were recruited from glaucoma and retina clinics at a tertiary eye care hospital and a physician's clinic. Non-mydriatic fundus photography was performed according to the disease-specific protocols. These images were graded by the AI system and specialist graders and comparatively analyzed. Results: Out of 1085 patients, 362 were seen at glaucoma clinics, 341 were seen at retina clinics, and 382 were seen at physician clinics. The kappa agreement between AI and the glaucoma grader was 85% [95% confidence interval (CI): 77.55–92.45%], and retina grading had 91.90% (95% CI: 87.78–96.02%). The retina grader from the glaucoma clinic had 85% agreement, and the glaucoma grader from the retina clinic had 73% agreement. The sensitivity and specificity of AI glaucoma grading were 79.37% (95% CI: 67.30–88.53%) and 99.45 (95% CI: 98.03–99.93), respectively; DR grading had 83.33% (95 CI: 51.59–97.91) and 98.86 (95% CI: 97.35–99.63). The cross-referral accuracy of DR and glaucoma was 89.57% and 95.43%, respectively. Conclusion: DL-based AI systems showed high sensitivity and specificity in both patients with DR and glaucoma; also, there was a good agreement between the specialist graders and the AI system

Comparative evaluation of visual outcomes and corneal asphericity after laser-assisted in situ keratomileusis with the six-dimension Amaris excimer laser system.

PURPOSE:To compare the visual and refractive outcomes after laser-assisted in situ keratomileusis (LASIK) surgery for correction of myopia or myopic astigmatism using a six-dimensional Amaris excimer laser. METHODS:In this retrospective cohort study, we enrolled 47 eyes of 28 patients (age: 19-36 years) with myopia or myopic astigmatism. We used the Custom Ablation Manager protocol and performed ablations with the SCHWIND AMARIS system. LASIK flaps were cut with an iFS Advanced Femtosecond Laser. Mean static (SCC) and dynamic cyclotorsion (DCC) were evaluated. Visual and refractive outcomes were evaluated during 6 months' follow-up. Corneal asphericity (Q-value) was analyzed at 4 months postoperatively. RESULTS:The spherical equivalent (SE) reduction was statistically significant reduce 1 day after refractive surgery (P < 0.001), with no additional significant changes during follow-up (P = 0.854). SCC registration rates were 81% in the Aberration-Free mode (AF) and 90% in the Corneal Wavefront mode (CW). SCC measurements were within ± 5 degrees in 57% (AF) and 68% (CW) of eyes. Mean DCC was within ± 1 degree in 96% (AF) or 95% (CW) of cases. At 6 months, the uncorrected distance visual acuity was 20/25 or better in all eyes. At last follow-up, both steep and flat keratometry values had significantly flattened in both groups (P < 0.001). Corneal asphericity also increased significantly during the postoperative period for an 8-mm corneal diameter (P < 0.001). CONCLUSIONS:LASIK for myopia or myopic compound astigmatism correction using the six-dimensional AMARIS 750S excimer laser is safe, effective, and predictable. Postoperative corneal asphericity can be analyzed by linear regression to predict the changes in postoperative corneal asphericity with this approach

Modified Dynamic Physical Model of Valence Change Mechanism Memristors

© 2022 American Chemical Society.Valence change-type resistance switching behaviors in oxides can be understood by well-established physical models describing the field-driven oxygen vacancy distribution change. In those models, electroformed residual oxygen vacancy filaments are crucial as they work as an electric field concentrator and limit the oxygen vacancy movement along the vertical direction. Therefore, their movement outward by diffusion is negligible. However, this situation may not be applicable in the electroforming-free system, where the field-driven movement is less prominent, and the isotropic oxygen vacancy diffusion by concentration gradient is more significant, which has not been given much consideration in the conventional model. Here, we propose a modified physical model that considers the change in the oxygen vacancies&apos; charged state depending on their concentrations and the resulting change in diffusivity during switching to interpret the electroforming-free device behaviors. The model suggests formation of an hourglass-shaped filament constituting a lower concentration of oxygen vacancies due to the fluid oxygen diffusion in the thin oxide. Consequently, the proposed model can explain the electroforming-free device behaviors, including the retention failure mechanism, and suggest an optimized filament configuration for improved retention characteristics. The proposed model can plausibly explain both the electroformed and the electroforming-free devices. Therefore, it can be a standard model for valence change memristors.N