Personalized modeling for prediction with decision-path models

Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three personalized methods that derive personalized decision-path models. We compared the performance of these methods to that of Classification And Regression Tree (CART) that is a population decision tree to predict seven different outcomes in five medical datasets. Two of the three personalized methods performed statistically significantly better on area under the ROC curve (AUC) and Brier skill score compared to CART. The personalized approach of learning decision path models is a new approach for predictive modeling that can perform better than a population approach

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases

BACKGROUND: Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL). METHODS: We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients. RESULTS: Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of discrimination due to a pattern of increased voxel-weight values in AD individuals was surprisingly high (ranging from approximately 20% to 40% depending on the imaging modality), located mainly in primary sensorimotor and visual cortices and subcortical nuclei. CONCLUSION: The MKL-ROI approach highlights the high discriminative weight of a subset of brain regions of known relevance to AD, the selection of which contributes to increased classification accuracy when applied to 18F-FDG-PET data. Moreover, the MKL-ROI approach demonstrates that brain regions typically spared in mild stages of AD also contribute substantially in the individual discrimination of AD patients from controls

Do topical repellents divert mosquitoes within a community? Health equity implications of topical repellents as a mosquito bite prevention tool.

OBJECTIVES: Repellents do not kill mosquitoes--they simply reduce human-vector contact. Thus it is possible that individuals who do not use repellents but dwell close to repellent users experience more bites than otherwise. The objective of this study was to measure if diversion occurs from households that use repellents to those that do not use repellents. METHODS: The study was performed in three Tanzanian villages using 15%-DEET and placebo lotions. All households were given LLINs. Three coverage scenarios were investigated: complete coverage (all households were given 15%-DEET), incomplete coverage (80% of households were given 15%-DEET and 20% placebo) and no coverage (all households were given placebo). A crossover study design was used and coverage scenarios were rotated weekly over a period of ten weeks. The placebo lotion was randomly allocated to households in the incomplete coverage scenario. The level of compliance was reported to be close to 100%. Mosquito densities were measured through aspiration of resting mosquitoes. Data were analysed using negative binomial regression models. FINDINGS: Repellent-users had consistently fewer mosquitoes in their dwellings. In villages where everybody had been given 15%-DEET, resting mosquito densities were fewer than half that of households in the no coverage scenario (Incidence Rate Ratio [IRR]=0.39 (95% confidence interval [CI]: 0.25-0.60); p<0.001). Placebo-users living in a village where 80% of the households used 15%-DEET were likely to have over four-times more mosquitoes (IRR=4.17; 95% CI: 3.08-5.65; p<0.001) resting in their dwellings in comparison to households in a village where nobody uses repellent. CONCLUSIONS: There is evidence that high coverage of repellent use could significantly reduce man-vector contact but with incomplete coverage evidence suggests that mosquitoes are diverted from households that use repellent to those that do not. Therefore, if repellents are to be considered for vector control, strategies to maximise coverage are required

Case study on the efficacy of a lanthanum-enriched clay (Phoslock®) in controlling eutrophication in Lake Het Groene Eiland (The Netherlands)

Lake Het Groene Eiland was created in the beginning of 2008 by construction of dikes for isolating it from the surrounding 220-ha water body. This so-called claustrum of 5 ha was treated using lanthanum-modified clay (Phoslock®) to control eutrophication and mitigate cyanobacterial nuisance. Cyanobacteria chlorophyll-a were significantly lower in the claustrum than those in the reference water body, where a massive bloom developed in summer, 2008. However, PO4-P and TP did not statistically differ in these two waters. TN and NO3-N were significantly lower in the claustrum, where dense submerged macrophytes beds developed. Lanthanum concentrations were elevated after the applications of the modified clay in the claustrum, but filterable lanthanum dropped rapidly below the Dutch standard of 10.1 μg l−1. During winter, dozens of Canada geese resided at the claustrum. Geese droppings contained an average of 2 mg PO4-P g−1 dry weight and 12 mg NH3-N g−1 dry weight and might present a growing source of nutrients to the water. Constructing the claustrum enabled unrestricted bathing in subsequent three summers, as no swimming bans had to be issued due to cyanobacteria blooms. However, the role of the modified clay in this positive outcome remains unclear, and longevity of the measures questionable.

Viability of MSSM scenarios at very large tan(beta)

We investigate the MSSM with very large tan(beta) > 50, where the fermion masses are strongly affected by loop-induced couplings to the "wrong" Higgs, imposing perturbative Yukawa couplings and constraints from flavour physics. Performing a low-energy scan of the MSSM with flavour-blind soft terms, we find that the branching ratio of B->tau nu and the anomalous magnetic moment of the muon are the strongest constraints at very large tan(beta) and identify the viable regions in parameter space. Furthermore we determine the scale at which the perturbativity of the Yukawa sector breaks down, depending on the low-energy MSSM parameters. Next, we analyse the very large tan(beta) regime of General Gauge Mediation (GGM) with a low mediation scale. We investigate the requirements on the parameter space and discuss the implied flavour phenomenology. We point out that the possibility of a vanishing Bmu term at a mediation scale M = 100 TeV is challenged by the experimental data on B->tau nu and the anomalous magnetic moment of the muon.Comment: 29 pages, 7 figures. v2: discussion in sections 1 and 4 expanded, conclusions unchanged. Matches version published in JHE

MAXIPOL: a balloon-borne experiment for measuring the polarization anisotropy of the cosmic microwave background radiation

We discuss MAXIPOL, a bolometric balloon-borne experiment designed to measure the E-mode polarization anisotropy of the cosmic microwave background radiation (CMB) on angular scales of 10 arcmin to 2 degrees. MAXIPOL is the first CMB experiment to collect data with a polarimeter that utilizes a rotating half-wave plate and fixed wire-grid polarizer. We present the instrument design, elaborate on the polarimeter strategy and show the instrument performance during flight with some time domain data. Our primary data set was collected during a 26 hour turnaround flight that was launched from the National Scientific Ballooning Facility in Ft. Sumner, New Mexico in May 2003. During this flight five regions of the sky were mapped. Data analysis is in progress

Higgs-mediated FCNCs: Natural Flavour Conservation vs. Minimal Flavour Violation

We compare the effectiveness of two hypotheses, Natural Flavour Conservation (NFC) and Minimal Flavour Violation (MFV), in suppressing the strength of flavour-changing neutral-currents (FCNCs) in models with more than one Higgs doublet. We show that the MFV hypothesis, in its general formulation, is more stable in suppressing FCNCs than the hypothesis of NFC alone when quantum corrections are taken into account. The phenomenological implications of the two scenarios are discussed analysing meson-antimeson mixing observables and the rare decays B -> mu+ mu-. We demonstrate that, introducing flavour-blind CP phases, two-Higgs doublet models respecting the MFV hypothesis can accommodate a large CP-violating phase in Bs mixing, as hinted by CDF and D0 data and, without extra free parameters, soften significantly in a correlated manner the observed anomaly in the relation between epsilon_K and S_psi_K.Comment: 27 pages, 4 figures. v3: minor modifications (typos corrected and few refs. added), conclusions unchanged; journal versio

Support vector machine-based classification of neuroimages in Alzheimer’s disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals

OBJECTIVE: To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (T1-MRI), F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and regional cerebral blood flow single-photon emission computed tomography (rCBF-SPECT) in Alzheimer's disease (AD). METHOD: Brain T1-MRI, FDG-PET and rCBF-SPECT scans were acquired from a sample of mild AD patients (n=20) and healthy elderly controls (n=18). SVM-based diagnostic accuracy indices were calculated using whole-brain information and leave-one-out cross-validation. RESULTS: The accuracy obtained using PET and SPECT data were similar. PET accuracy was 68∼71% and area under curve (AUC) 0.77∼0.81; SPECT accuracy was 68∼74% and AUC 0.75∼0.79, and both had better performance than analysis with T1-MRI data (accuracy of 58%, AUC 0.67). The addition of PET or SPECT to MRI produced higher accuracy indices (68∼74%; AUC: 0.74∼0.82) than T1-MRI alone, but these were not clearly superior to the isolated neurofunctional modalities. CONCLUSION: In line with previous evidence, FDG-PET and rCBF-SPECT more accurately identified patients with AD than T1-MRI, and the addition of either PET or SPECT to T1-MRI data yielded increased accuracy. The comparable SPECT and PET performances, directly demonstrated for the first time in the present study, support the view that rCBF-SPECT still has a role to play in AD diagnosis