3D Model Retrieval with Spherical Harmonics and Moments

We consider 3D object retrieval in which a polygonal mesh serves as a query and similar objects are retrieved from a collection of 3D objects. Algorithms proceed first by a normalization step in which models are transformed into canonical coordinates. Second, feature vectors are extracted and compared with those derived from normalized models in the search space. In the feature vector space nearest neighbors are computed and ranked. Retrieved objects are displayed for inspection, selection, and processing. Our feature vectors are based on rays cast from the center of mass of the object. For each ray the object extent in the ray direction yields a sample of a function on the sphere. We compared two kinds of representations of this function, namely spherical harmonics and moments. Our empirical comparison using precision-recall diagrams for retrieval results in a data base of 3D models showed that the method using spherical harmonics performed better

A review on data stream classification

At this present time, the significance of data streams cannot be denied as many researchers have placed their focus on the research areas of databases, statistics, and computer science. In fact, data streams refer to some data points sequences that are found in order with the potential to be non-binding, which is generated from the process of generating information in a manner that is not stationary. As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies

Fast, scalable, Bayesian spike identification for multi-electrode arrays

We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes overlap, and accounts for intrinsic variability of spikes from each unit. As MEAs grow larger, it is important to find spike-identification methods that are scalable, that is, the computational cost of spike fitting should scale well with the number of units observed. Our algorithm accomplishes this goal, and is fast, because it exploits the spatial locality of each unit and the basic biophysics of extracellular signal propagation. Human intervention is minimized and streamlined via a graphical interface. We illustrate our method on data from a mammalian retina preparation and document its performance on simulated data consisting of spikes added to experimentally measured background noise. The algorithm is highly accurate

External Validation and Comparison of Prostate Cancer Risk Calculators Incorporating Multiparametric Magnetic Resonance Imaging for Prediction of Clinically Significant Prostate Cancer

PURPOSE: To externally validate recently published prostate cancer risk calculators (PCa-RCs) incorporating multiparametric magnetic resonance imaging (mpMRI) for the prediction of clinically significant prostate cancer (csPCa) and compare their performance to mpMRI-naïve PCa-RCs. MATERIAL AND METHODS: Men without previous PCa diagnosis undergoing transperineal template saturation prostate biopsy with fusion-guided targeted biopsy between 11/2014 and 03/2018 in our academic tertiary referral center were identified. Any Gleason pattern ≥4 was defined to be csPCa. Predictors (age, PSA, DRE, prostate volume, family history, previous prostate biopsy and highest region of interest according to PIRADS) were retrospectively collected. Four mpMRI-PCa-RCs and two mpMRI-naïve PCa-RCs were evaluated for their discrimination, calibration and clinical net benefit using a ROC analysis, calibration plots and a decision curve analysis, respectively. RESULTS: Out of 468 men, 193 (41%) were diagnosed with csPCa. Three mpMRI-PCa-RCs showed similar discrimination with area-underneath-the-receiver-operating-characteristic-curves (AUC) from 0.83 to 0.85, which was significantly higher than the other PCa-RCs (AUCs: 0.69-0.74). Calibration-in-the-large showed minimal deviation from the true amount of csPCa by 2% for two mpMRI-PCa-RCs, while the other PCa-RCs showed worse calibration (11-27%). A clinical net benefit could only be observed for three mpMRI-PCa-RCs at biopsy thresholds ≥15%, while none of the six investigated PCa-RCs demonstrated clinical utility against a biopsy all strategy at thresholds <15%. CONCLUSIONS: Performance of the mpMRI-PCa-RCs varies, but they generally outperform mpMRI-naïve PCa-RCs in regard to discrimination, calibration and clinical usefulness. External validation in other biopsy settings is highly encouraged

Clust-IT:Clustering-Based Intrusion Detection in IoT Environments

Low-powered and resource-constrained devices are forming a greater part of our smart networks. For this reason, they have recently been the target of various cyber-attacks. However, these devices often cannot implement traditional intrusion detection systems (IDS), or they can not produce or store the audit trails needed for inspection. Therefore, it is often necessary to adapt existing IDS systems and malware detection approaches to cope with these constraints. We explore the application of unsupervised learning techniques, specifically clustering, to develop a novel IDS for networks composed of low-powered devices. We describe our solution, called Clust-IT (Clustering of IoT), to manage heterogeneous data collected from cooperative and distributed networks of connected devices and searching these data for indicators of compromise while remaining protocol agnostic. We outline a novel application of OPTICS to various available IoT datasets, composed of both packet and flow captures, to demonstrate the capabilities of the proposed techniques and evaluate their feasibility in developing an IoT IDS

Interactive decision support in hepatic surgery

BACKGROUND: Hepatic surgery is characterized by complicated operations with a significant peri- and postoperative risk for the patient. We developed a web-based, high-granular research database for comprehensive documentation of all relevant variables to evaluate new surgical techniques. METHODS: To integrate this research system into the clinical setting, we designed an interactive decision support component. The objective is to provide relevant information for the surgeon and the patient to assess preoperatively the risk of a specific surgical procedure. Based on five established predictors of patient outcomes, the risk assessment tool searches for similar cases in the database and aggregates the information to estimate the risk for an individual patient. RESULTS: The physician can verify the analysis and exclude manually non-matching cases according to his expertise. The analysis is visualized by means of a Kaplan-Meier plot. To evaluate the decision support component we analyzed data on 165 patients diagnosed with hepatocellular carcinoma (period 1996–2000). The similarity search provides a two-peak distribution indicating there are groups of similar patients and singular cases which are quite different to the average. The results of the risk estimation are consistent with the observed survival data, but must be interpreted with caution because of the limited number of matching reference cases. CONCLUSION: Critical issues for the decision support system are clinical integration, a transparent and reliable knowledge base and user feedback

Impact of cryopreservation on tetramer, cytokine flow cytometry, and ELISPOT

BACKGROUND: Cryopreservation of PBMC and/or overnight shipping of samples are required for many clinical trials, despite their potentially adverse effects upon immune monitoring assays such as MHC-peptide tetramer staining, cytokine flow cytometry (CFC), and ELISPOT. In this study, we compared the performance of these assays on leukapheresed PBMC shipped overnight in medium versus cryopreserved PBMC from matched donors. RESULTS: Using CMV pp65 peptide pool stimulation or pp65 HLA-A2 tetramer staining, there was significant correlation between shipped and cryopreserved samples for each assay (p ≤ 0.001). The differences in response magnitude between cryopreserved and shipped PBMC specimens were not significant for most antigens and assays. There was significant correlation between CFC and ELISPOT assay using pp65 peptide pool stimulation, in both shipped and cryopreserved samples (p ≤ 0.001). Strong correlation was observed between CFC (using HLA-A2-restricted pp65 peptide stimulation) and tetramer staining (p < 0.001). Roughly similar sensitivity and specificity were observed between the three assays and between shipped and cryopreserved samples for each assay. CONCLUSION: We conclude that all three assays show concordant results on shipped versus cryopreserved specimens, when using a peptide-based readout. The assays are also concordant with each other in pair wise comparisons using equivalent antigen systems

Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

Objective: We compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts, in which some cohorts do not collect some risk factors at all, and developed an online risk prediction tool that accommodates missing risk factors from the end-user. Study Design and Setting: Ten North American and European cohorts from the Prostate Biopsy Collaborative Group (PBCG) were used for fitting a risk prediction tool for clinically significant prostate cancer, defined as Gleason grade group greater or equal 2 on standard TRUS prostate biopsy. One large European PBCG cohort was withheld for external validation, where calibration-in-the-large (CIL), calibration curves, and area-underneath-the-receiver-operating characteristic curve (AUC) were evaluated. Ten-fold leave-one-cohort-internal validation further validated the optimal missing data approach. Results: Among 12,703 biopsies from 10 training cohorts, 3,597 (28%) had clinically significant prostate cancer, compared to 1,757 of 5,540 (32%) in the external validation cohort. In external validation, the available cases method that pooled individual patient data containing all risk factors input by an end-user had best CIL, under-predicting risks as percentages by 2.9% on average, and obtained an AUC of 75.7%. Imputation had the worst CIL (-13.3%). The available cases method was further validated as optimal in internal cross-validation and thus used for development of an online risk tool. For end-users of the risk tool, two risk factors were mandatory: serum prostate-specific antigen (PSA) and age, and ten were optional: digital rectal exam, prostate volume, prior negative biopsy, 5-alpha-reductase-inhibitor use, prior PSA screen, African ancestry, Hispanic ethnicity, first-degree prostate-, breast-, and second-degree prostate-cancer family history

Budesonide/formoterol as effective as prednisolone plus formoterol in acute exacerbations of COPD A double-blind, randomised, non-inferiority, parallel-group, multicentre study

<p>Abstract</p> <p>Background</p> <p>Oral corticosteroids and inhaled bronchodilators with or without antibiotics represent standard treatment of COPD exacerbations of moderate severity. Frequent courses of oral steroids may be a safety issue. We wanted to evaluate in an out-patient setting whether a 2-week course of inhaled budesonide/formoterol would be equally effective for treatment of acute COPD exacerbations as standard therapy in patients judged by the investigator not to require hospitalisation.</p> <p>Methods</p> <p>This was a double-blind, randomised, non-inferiority, parallel-group, multicentre study comparing two treatment strategies; two weeks' treatment with inhaled budesonide/formoterol (320/9 μg, qid) was compared with prednisolone (30 mg once daily) plus inhaled formoterol (9 μg bid) in patients with acute exacerbations of COPD attending a primary health care centre. Inclusion criteria were progressive dyspnoea for less than one week, FEV₁30–60% of predicted normal after acute treatment with a single dose of oral corticosteroid plus nebulised salbutamol/ipratropium bromide and no requirement for subsequent immediate hospitalisation, i.e the clinical status after the acute treatment allowed for sending the patient home.</p> <p>A total of 109 patients (mean age 67 years, 33 pack-years, mean FEV₁45% of predicted) were randomized to two weeks' double-blind treatment with budesonide/formoterol or prednisolone plus formoterol and subsequent open-label budesonide/formoterol (320/9 μg bid) for another 12 weeks. Change in FEV₁was the primary efficacy variable. Non-inferiority was predefined.</p> <p>Results</p> <p>Non-inferiority of budesonide/formoterol was proven because the lower limit of FEV₁-change (97.5% CI) was above 90% of the efficacy of the alternative treatment. Symptoms, quality of life, treatment failures, need for reliever medication (and exacerbations during follow-up) did not differ between the groups. No safety concerns were identified.</p> <p>Conclusion</p> <p>High dose budesonide/formoterol was as effective as prednisolone plus formoterol for the ambulatory treatment of acute exacerbations in non-hospitalized COPD patients. An early increase in budesonide/formoterol dose may therefore be tried before oral corticosteroids are used.</p> <p>Clinical trial registration</p> <p>NCT00259779</p