What it Thinks is Important is Important: Robustness Transfers through Input Gradients

Adversarial perturbations are imperceptible changes to input pixels that can change the prediction of deep learning models. Learned weights of models robust to such perturbations are previously found to be transferable across different tasks but this applies only if the model architecture for the source and target tasks is the same. Input gradients characterize how small changes at each input pixel affect the model output. Using only natural images, we show here that training a student model's input gradients to match those of a robust teacher model can gain robustness close to a strong baseline that is robustly trained from scratch. Through experiments in MNIST, CIFAR-10, CIFAR-100 and Tiny-ImageNet, we show that our proposed method, input gradient adversarial matching, can transfer robustness across different tasks and even across different model architectures. This demonstrates that directly targeting the semantics of input gradients is a feasible way towards adversarial robustness.Comment: Accepted as Oral in CVPR 2020, Camera-Ready Versio

Modular stem in total hip arthroplasty for patients with trochanter valgus deformity: surgical technique and case series.

BACKGROUND: Trochanter valgus deformity (TVD) is a rare condition of total hip arthroplasty (THA). Femoral osteotomy could be required in correcting the deformity to implant femoral stem in severe TVD. In this study, we described one unpublished technique of reverse sleeve of S-ROM to get through the complex situation. This study aimed to summarize and evaluate its technical challenges, safety and effectiveness. METHODS: From January 2006 to December 2014, we enrolled patients whose sleeves were implanted towards the great trochanter in THA with TVD. Their demographics, perioperative and postoperative information were recorded. To explore its indication, we measured and analyzed the ratio of greater trochanter/lesser trochanter (G/L ratio) and trochanter valgus angle (TVA). RESULTS: Twelve patients (1 male and 11 female, average age 42.30 ± 10.23) had mean follow-up of 6 years. Among them, only two patients had intraoperative femoral fracture. The survivorship of femoral prosthesis was 100%. The Harris hip score (HHS) increased from preoperative 34.31 ± 14.43 to postoperative 84.12 ± 11.33. All patients\u27 G/L ratio were larger than 1.50. CONCLUSIONS: The reverse sleeve of S-ROM was a reliable method for the patients with severe TVD, which brought satisfying clinical outcomes in mid-term follow-up

Season of the year influences infection rates following total hip arthroplasty

To research the influence of season of the year on periprosthetic joint infections. METHODS We conducted a retrospective review of the entire Medicare files from 2005 to 2014. Seasons were classified as spring, summer, fall or winter. Regional variations were accounted for by dividing patients into four geographic regions as per the United States Census Bureau (Northeast, Midwest, West and South). Acute postoperative infection and deep periprosthetic infections within 90 d after surgery were tracked. RESULTS In all regions, winter had the highest incidence of periprosthetic infections (mean 0.98%, SD 0.1%) and was significantly higher than other seasons in the Midwest, South and West (P \u3c 0.05 for all) but not the Northeast (P = 0.358). Acute postoperative infection rates were more frequent in the summer and were significantly affected by season of the year in the West. CONCLUSION Season of the year is a risk factor for periprosthetic joint infection following total hip arthroplasty (THA). Understanding the influence of season on outcomes following THA is essential when risk-stratifying patients to optimize outcomes and reduce episode of care costs. © The Author(s) 2017

Total knee arthroplasty using a hybrid navigation technique

The use of computer navigation is becoming a well-recognized technical alternative to conventional total knee arthroplasty (TKA). However, computer navigation has a substantial learning curve and the use of commercially available navigation systems increases surgical time. In addition, the potential risks associated with the navigation TKA, such as, registration errors, notching of the anterior femoral cortex, oversizing of the femoral component, and overresection must be taken into consideration. On the other hand, conventional techniques are familiar and intuitive to most practicing surgeons, and thus, are easier to perform and are less prone to anterior notching and femoral component oversizing. However, conventional techniques have greater risks of inaccurate and inconsistent component alignment than computer navigation. This paper describes a novel technique that combines computer navigation and conventional TKA

Should We Use Preoperative Epoetin-α in the Mildly Anemic Patient Undergoing Simultaneous Total Knee Arthroplasty?

Simultaneous knee arthroplasty is associated with significant blood loss. To prevent transfusion, three preoperative doses of epoetin-α were offered to mildly anemic simultaneous knee arthroplasty patients. A retrospective review, using ICD-9 codes, identified twenty patients from 2007-2009. Epoetin-α increased hemoglobin levels preoperatively (12.6 to 13.9,

Satellite Workshop On Language, Artificial Intelligence and Computer Science for Natural Language Processing Applications (LAICS-NLP): Discovery of Meaning from Text

This paper proposes a novel method to disambiguate important words from a collection of documents. The hypothesis that underlies this approach is that there is a minimal set of senses that are significant in characterizing a context. We extend Yarowsky’s one sense per discourse [13] further to a collection of related documents rather than a single document. We perform distributed clustering on a set of features representing each of the top ten categories of documents in the Reuters-21578 dataset. Groups of terms that have a similar term distributional pattern across documents were identified. WordNet-based similarity measurement was then computed for terms within each cluster. An aggregation of the associations in WordNet that was employed to ascertain term similarity within clusters has provided a means of identifying clusters’ root senses