Video-assisted thoracic surgery diagnosis of thoracic spinal tuberculosis.

Tuberculous spondylitis is rare in economically well-developed countries. MRI is the most sensitive radiologic method of diagnosis. CT-guided fine needle aspiration can be an appropriate method for obtaining samples for culture, with positive cultures in 25 to 89% of cases. However, it can take >6 weeks for specimens to grow, and it is essential to have adequate culture and sensitivity studies for the diagnosis and treatment of mycobacterial diseases. We propose a minimally invasive diagnostic approach that ensures that adequate surgical specimens are obtained prior to initiating treatment.

Classification of urban multi-angular image sequences by aligning their manifolds

When dealing with multi-angular image sequences, problems of reflectance changes due either to illumination and acquisition geometry, or to interactions with the atmosphere, naturally arise. These phenomena interplay with the scene and lead to a modification of the measured radiance: for example, according to the angle of acquisition, tall objects may be seen from top or from the side and different light scatterings may affect the surfaces. This results in shifts in the acquired radiance, that make the problem of multi-angular classification harder and might lead to catastrophic results, since surfaces with the same reflectance return significantly different signals. In this paper, rather than performing atmospheric or bi-directional reflection distribution function (BRDF) correction, a non-linear manifold learning approach is used to align data structures. This method maximizes the similarity between the different acquisitions by deforming their manifold, thus enhancing the transferability of classification models among the images of the sequence.

Serrated polyps of the colon: how reproducible is their classification?

For several years, the lack of consensus on definition, nomenclature, natural history, and biology of serrated polyps (SPs) of the colon has created considerable confusion among pathologists. According to the latest WHO classification, the family of SPs comprises hyperplastic polyps (HPs), sessile serrated adenomas/polyps (SSA/Ps), and traditional serrated adenomas (TSAs). The term SSA/P with dysplasia has replaced the category of mixed hyperplastic/adenomatous polyps (MPs). The present study aimed to evaluate the reproducibility of the diagnosis of SPs based on currently available diagnostic criteria and interactive consensus development. In an initial round, H&E slides of 70 cases of SPs were circulated among participating pathologists across Europe. This round was followed by a consensus discussion on diagnostic criteria. A second round was performed on the same 70 cases using the revised criteria and definitions according to the recent WHO classification. Data were evaluated for inter-observer agreement using Kappa statistics. In the initial round, for the total of 70 cases, a fair overall kappa value of 0.318 was reached, while in the second round overall kappa value improved to moderate (kappa = 0.557; p < 0.001). Overall kappa values for each diagnostic category also significantly improved in the final round, reaching 0.977 for HP, 0.912 for SSA/P, and 0.845 for TSA (p < 0.001). The diagnostic reproducibility of SPs improves when strictly defined, standardized diagnostic criteria adopted by consensus are applied.

Age vs. Experience: Evaluation of a Video Feedback Intervention for Newly Licensed Teen Drivers, TPF-5(207), 2013

This project examines the effects of age, experience, and video-based feedback on the rate and type of safety-relevant events captured on video event recorders in the vehicles of three groups of newly licensed young drivers: 1. 14.5- to 15.5-year-old drivers who hold a minor school license (see Appendix A for the provisions of the Iowa code governing minor school licenses); 2. 16-year-old drivers with an intermediate license who are driving unsupervised for the first time; 3. 16-year-old drivers with an intermediate license who previously drove unsupervised for at least four months with a school license. METHODS: The young drivers’ vehicles were equipped with an event-triggered video recording device for 24 weeks. Half of the participants received feedback regarding their driving, and the other half received no feedback at all and served as a control group. The number of safety-relevant events per 1,000 miles (i.e., “event rate”) was analyzed for 90 participants who completed the study. RESULTS: On average, the young drivers who received the video-based intervention had significantly lower event rates than those in the control group. This finding was true for all three groups. An effect of experience was seen for drivers in the control group; the 16-year-olds with driving experience had significantly lower event rates than the 16-year-olds without experience. When the intervention concluded, an increase in event rate was seen for the school license holders, but not for either group of 16-year-old drivers. There is strong evidence that giving young drivers video-based feedback, regardless of their age or level of driving experience, is effective in reducing the rate of safety-relevant events relative to a control group who do not receive feedback. Specific comparisons with regard to age and experience indicated that the age of the driver did not have an effect on the rate of safety-events, while experience did. Young drivers with six months or more of additional experience behind the wheel had nearly half as many safety-relevant events as those without that experience.

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.