Random forest prediction of Alzheimer's disease using pairwise selection from time series data

Time-dependent data collected in studies of Alzheimer's disease usually has missing and irregularly sampled data points. For this reason time series methods which assume regular sampling cannot be applied directly to the data without a pre-processing step. In this paper we use a machine learning method to learn the relationship between pairs of data points at different time separations. The input vector comprises a summary of the time series history and includes both demographic and non-time varying variables such as genetic data. The dataset used is from the 2017 TADPOLE grand challenge which aims to predict the onset of Alzheimer's disease using including demographic, physical and cognitive data. The challenge is a three-fold diagnosis classification into AD, MCI and control groups, the prediction of ADAS-13 score and the normalised ventricle volume. While the competition proceeds, forecasting methods may be compared using a leaderboard dataset selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and with standard metrics for measuring accuracy. For diagnosis, we find an mAUC of 0.82, and a classification accuracy of 0.73. The results show that the method is effective and comparable with other methods.Comment: 6 pages, 1 figure, 6 table

Non-cholesteatomatous suppurative otitis media: facial nerve palsy in an immunocompromised patient

A 47-year-old man developed a complete facial nerve palsy secondary to non-cholesteatomatous suppurative otitis media. At operation, this was seen to be due to destruction of the nerve from halfway along the horizontal segment to a point just distal to the second genu. The history of recent renal transplantation and subsequent immunosuppression was judged to be significant in the pathogenesis of the palsy

Rough paths in idealized financial markets

This paper considers possible price paths of a financial security in an idealized market. Its main result is that the variation index of typical price paths is at most 2, in this sense, typical price paths are not rougher than typical paths of Brownian motion. We do not make any stochastic assumptions and only assume that the price path is positive and right-continuous. The qualification "typical" means that there is a trading strategy (constructed explicitly in the proof) that risks only one monetary unit but brings infinite capital when the variation index of the realized price path exceeds 2. The paper also reviews some known results for continuous price paths and lists several open problems.Comment: 21 pages, this version adds (in Appendix C) a reference to new results in the foundations of game-theoretic probability based on Hardin and Taylor's work on hat puzzle

A simple method to assess the oxidative susceptibility of low density lipoproteins

BACKGROUND: Oxidative modification of low density lipoproteins (LDL) is recognized as one of the major processes involved in atherogenesis. The in vitro standardized measurement of LDL oxidative susceptibility could thus be of clinical significance. The aim of the present study was to establish a method which would allow the evaluation of oxidative susceptibility of LDL in the general clinical laboratory. RESULTS: LDL was isolated from human plasma by selective precipitation with amphipathic polymers. The ability of LDL to form peroxides was assessed by measuring thiobarbituric acid reactive substances (TBARS) after incubation with Cu(2+) and H(2)O(2). Reaction kinetics showed a three-phase pattern (latency, propagation and decomposition phases) which allowed us to select 150 min as the time point to stop the incubation by cooling and EDTA addition. The mixture Cu(2+)/H(2)O(2) yielded more lipoperoxides than each one on its own at the same time end-point. Induced peroxidation was measured in normal subjects and in type 2 diabetic patients. In the control group, results were 21.7 ± 1.5 nmol MDA/mg LDL protein, while in the diabetic group results were significantly increased (39.0 ± 3.0 nmol MDA/mg LDL protein; p < 0.001). CONCLUSION: a simple and useful method is presented for the routine determination of LDL susceptibility to peroxidation in a clinical laboratory