Fish Grubs in Freshwater Ponds and Lakes.

8 p

Anchor Parasites of Fishes.

2 p

Ich Disease of Fishes.

4 p

Ich Disease of Fishes.

6 p

The Incremental Multiresolution Matrix Factorization Algorithm

Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices -- an important aspect in the success of many vision problems. Our new algorithm, the incremental multiresolution matrix factorization, uncovers such structure one feature at a time, and hence scales well to large matrices. We describe how this multiscale analysis goes much farther than what a direct global factorization of the data can identify. We evaluate the efficacy of the resulting factorizations for relative leveraging within regression tasks using medical imaging data. We also use the factorization on representations learned by popular deep networks, providing evidence of their ability to infer semantic relationships even when they are not explicitly trained to do so. We show that this algorithm can be used as an exploratory tool to improve the network architecture, and within numerous other settings in vision.Comment: Computer Vision and Pattern Recognition (CVPR) 2017, 10 page

Speeding up Permutation Testing in Neuroimaging

Multiple hypothesis testing is a significant problem in nearly all neuroimaging studies. In order to correct for this phenomena, we require a reliable estimate of the Family-Wise Error Rate (FWER). The well known Bonferroni correction method, while simple to implement, is quite conservative, and can substantially under-power a study because it ignores dependencies between test statistics. Permutation testing, on the other hand, is an exact, non-parametric method of estimating the FWER for a given $\alpha$-threshold, but for acceptably low thresholds the computational burden can be prohibitive. In this paper, we show that permutation testing in fact amounts to populating the columns of a very large matrix ${\bf P}$. By analyzing the spectrum of this matrix, under certain conditions, we see that ${\bf P}$ has a low-rank plus a low-variance residual decomposition which makes it suitable for highly sub--sampled --- on the order of $0.5\%$ --- matrix completion methods. Based on this observation, we propose a novel permutation testing methodology which offers a large speedup, without sacrificing the fidelity of the estimated FWER. Our evaluations on four different neuroimaging datasets show that a computational speedup factor of roughly $50\times$ can be achieved while recovering the FWER distribution up to very high accuracy. Further, we show that the estimated $\alpha$-threshold is also recovered faithfully, and is stable.Comment: NIPS 1

Fish Grubs in Freshwater Ponds and Lakes.

8 p

Oral Administration of Antibiotics to Fishes.

2 p

Risk of neuropsychiatric and cardiovascular adverse events following treatment with varenicline and nicotine replacement therapy in the UK Clinical Practice Research Datalink:a case-crossover study

BACKGROUND AND AIMS: Varenicline and nicotine replacement therapy (NRT) are the most commonly used medications to quit smoking. Given their widespread use, monitoring adverse risks remains important. This study aimed to estimate the neuropsychiatric and cardiovascular risks associated with varenicline and NRT as used in routine UK care.DESIGN: Case crossover study.SETTING: UK based electronic primary care records in the Clinical Practice Research Datalink from 2006 to 2015 linked to hospital and mortality datasets.PARTICIPANTS: Adult smokers (n=?) observed in periods when exposed and not exposed to either varenicline or NRT.MEASUREMENTS: Main outcomes included suicide, self-harm, myocardial infarction (MI), all-cause death and cause-specific death (MI, chronic obstructive pulmonary disease (COPD)). In primary analyses, conditional logistic regression was used to compare the chance of varenicline or NRT exposure in the risk period (90 days prior to the event) with the chance of exposure in an earlier single reference period (91-180 days prior to the event) or multiple 90-day reference periods to increase statistical power.FINDINGS: In the primary analyses, findings were inconclusive for the associations between varenicline and the main outcomes using a single reference period, whilst NRT was associated with MI (Odds ratio (OR) 1.40, 95% Confidence interval (CI) 1.18-1.67). Using multiple reference periods, varenicline was associated with an increased risk of self-harm (OR 1.32, 95% CI 1.12-1.56) and suicide (OR 3.56, 95% CI 1.32-9.60) but a reduction in all-cause death (OR 0.75, 95% CI 0.61-0.93). NRT was associated with MI (OR 1.54, 95% CI 1.36-1.74), self-harm (OR 1.30, 95% CI 1.18-1.44), and deaths from MI (OR 1.53, 95% CI 1.11-2.10), COPD (OR 1.33, 95% CI 1.14-1.56) and all causes (OR 1.28, 95% CI 1.18-1.40) when using multiple reference periods.CONCLUSIONS: There appear to be positive associations between 1) nicotine replacement therapy (NRT) and myocardial infarction, death, and risk of self-harm and 2) varenicline and increased risk of self-harm and suicide, as well as a negative association between varenicline and all-cause death. The associations may not be causal. They may reflect health changes at the time of smoking cessation (NRT is prescribed for people with cardiac problems) or be associated with quit attempts (exposure to both medicines was associated with self-harm).</p