Yahoo!

About: Yahoo! is a company organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Web search query. The organization has 26749 authors who have published 29915 publications receiving 732583 citations. The organization is also known as: Yahoo! Inc. & Maudwen-Yahoo! Inc.

A novel patient-specific navigational template for cervical pedicle screw placement.

Abstract: STUDY DESIGN.: Prospective trial. OBJECTIVE.: To develop and validate a novel, patient-specific navigational template for cervical pedicle placement. SUMMARY OF BACKGROUND DATA.: Owing to the narrow bony anatomy and the proximity to the vertebral artery and the spinal cord, cervical instrumentation procedures demand the need for a precise technique for screw placement. PATIENT.: Specific drill template with preplanned trajectory has been thought as a promising solution for cervical pedicle screw placement. METHODS.: Patients with cervical spinal pathology (n = 25) requiring instrumentation were recruited. Volumetric CT scan was performed on each desired cervical vertebra and a 3-dimensional reconstruction model was generated from the scan data. Using reverse engineering technique, the optimal screw size and orientation were determined and a drill template was designed with a surface that is the inverse of the posterior vertebral surface. The drill template and its corresponding vertebra were manufactured using rapid prototyping technique and tested for violations. The navigational template was sterilized and used intraoperatively to assist with the placement of cervical screws. In total, 88 screws were inserted into levels C2-C7 with 2 to 6 screw in each patient. After surgery, the positions of the pedicle screws were evaluated using CT scan and graded for validation. RESULTS.: This method showed its ability to customize the placement and the size of each screw based on the unique morphology of the cervical vertebra. In all the cases, it was relatively very easy to manually place the drill template on the lamina of the vertebral body during the surgery. The required time between fixation of the template to the lamina and insertion of the pedicle screws was about 80 seconds. Of the 88 screws, 71 screws had no deviation and 14 screws had deviation <2 mm, 1 screw had a deviation between 2 to 4 mm and there were no misplacements. Fluoroscopy was used only once for every patient after the insertion of all the pedicle screws. CONCLUSION.: The authors have developed a novel patient-specific navigational template for cervical pedicle screw placement with good applicability and high accuracy. This method significantly reduces the operation time and radiation exposure for the members of the surgical team. The potential use of such a navigational template to insert cervical pedicle screws is promising. This technique has been clinically validated to provide an accurate trajectory for pedicle screw placement in the cervical spine.

Learning Optimal Seeds for Diffusion-Based Salient Object Detection

Abstract: In diffusion-based saliency detection, an image is partitioned into superpixels and mapped to a graph, with superpixels as nodes and edge strengths proportional to superpixel similarity Saliency information is then propagated over the graph using a diffusion process, whose equilibrium state yields the object saliency map The optimal solution is the product of a propagation matrix and a saliency seed vector that contains a prior saliency assessment This is obtained from either a bottom-up saliency detector or some heuristics In this work, we propose a method to learn optimal seeds for object saliency Two types of features are computed per superpixel: the bottom-up saliency of the superpixel region and a set of mid-level vision features informative of how likely the superpixel is to belong to an object The combination of features that best discriminates between object and background saliency is then learned, using a large-margin formulation of the discriminant saliency principle The propagation of the resulting saliency seeds, using a diffusion process, is finally shown to outperform the state of the art on a number of salient object detection datasets

Multi-way Clustering on Relation Graphs.

Abstract: A number of real-world domains such as social networks and e-commerce involve heterogeneous data that describes relations between multiple classes of entities. Understanding the natural structure of this type of heterogeneous relational data is essential both for exploratory analysis and for performing various predictive modeling tasks. In this paper, we propose a principled multi-way clustering framework for relational data, wherein different types of entities are simultaneously clustered based not only on their intrinsic attribute values, but also on the multiple relations between the entities. To achieve this, we introduce a relation graph model that describes all the known relations between the different entity classes, in which each relation between a given set of entity classes is represented in the form of multi-modal tensor over an appropriate domain. Our multi-way clustering formulation is driven by the objective of capturing the maximal “information” in the original relation graph, i.e., accurately approximating the set of tensors corresponding to the various relations. This formulation is applicable to all Bregman divergences (a broad family of loss functions that includes squared Euclidean distance, KL-divergence), and also permits analysis of mixed data types using convex combinations of appropriate Bregman loss functions. Furthermore, we present a large family of structurally different multi-way clustering schemes that preserve various linear summary statistics of the original data. We accomplish the above generalizations by extending a recently proposed key theoretical result, namely the minimum Bregman information principle [1], to the relation graph setting. We also describe an efficient multi-way clustering algorithm based on alternate minimization that generalizes a number of other recently proposed clustering methods. Empirical results on datasets obtained from real-world domains (e.g., movie recommendations, newsgroup articles) demonstrate the generality and efficacy of our framework.

Efficacy and safety of tanezumab versus naproxen in the treatment of chronic low back pain.

Abstract: Tanezumab is a humanized monoclonal antibody that specifically inhibits nerve growth factor as a treatment for chronic pain. This phase IIB study investigated the efficacy and safety of tanezumab for chronic low back pain vs placebo and naproxen. Patients (N=1347) received intravenous tanezumab (5, 10, or 20mg every 8weeks), naproxen (500mg twice daily), or placebo. The primary efficacy end point was mean change in daily average low back pain intensity (LBPI) from baseline to week 16. Secondary end points included mean change from baseline to week 16 in the Roland Morris Disability Questionnaire and Patient's Global Assessment (PGA) of low back pain. Tanezumab 10 and 20mg had similar efficacy profiles and significantly improved LBPI, Roland Morris Disability Questionnaire, and PGA scores vs both placebo and naproxen (P⩽.05). Tanezumab 5mg provided improvement of PGA scores vs placebo (P⩽.05), and naproxen resulted in significant improvement of LBPI vs placebo (P⩽.05). Adverse event incidence was comparable across tanezumab doses but higher than with placebo or naproxen. Arthralgia, pain in extremity, headache, and paresthesia were the most commonly reported adverse events by tanezumab-treated patients. The most frequently reported adverse events resulting in discontinuation of tanezumab treatment were arthralgia and paresthesia; the highest frequency was observed with tanezumab 20mg (both 1.4%). Serious adverse event incidence was similar across treatments. In conclusion, tanezumab provided significantly greater improvement in pain, function, and global scores vs placebo and naproxen in patients with chronic low back pain.

System and method for delivery of augmented messages

Abstract: The disclosure describes systems and methods delivering communications associated with delivery conditions in which the occurrence of the delivery condition is determined by monitoring information received from a plurality of sources via multiple communication channels. The message delivery systems allow messages to be delivered to any “Who, What, When, Where” from any “Who, What, When, Where” upon the detection of an occurrence of one or more “Who, What, When, Where” delivery conditions. A message (which may be any data object including text-based messages, audio-based message such as voicemail or other audio such as music or video-based prerecorded messages) is delivered in accordance with delivery conditions based on any available data, including topical, spatial, temporal, and/or social data. Furthermore, because the systems coordinate delivery of messages via multiple communication channels and through multiple devices, the communication channel for delivery of a message may be dynamically determined based on the delivery conditions.