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We created an allelic imbalance detection pipeline, AA-ALIGNER, to remove reference mapping biases influencing allelic imbalance detection and evaluate accuracy of allelic imbalance predictions in the absence of complete genotype data.

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Hund et al. (2002) presented various methods of outlier detection and evaluated robustness tests with different experimental designs.

In addition to implementing the framework's content and context detection, and evaluating three large datasets using each module, we have also explored the random positive detection module.

This study assessed the prevalence of pulmonary tuberculosis through active case detection and evaluated predictors of pulmonary tuberculosis among residents of two peri-urban neighbourhoods of Karachi, Pakistan.

We have also done variable clustering that can be helpful in identifying risk factors, developing prognostic models and improving existing diagnosis and detection, and evaluating new laboratory diagnostic methods.

This allowed us to systematically vary the parameters critical for detection, such as SNR and detection thresholds, and evaluate the performance in terms of the probability of correct detection (Pcd) and probability of false alarm (Pfa).

A simulator is created to simulate the intrusion detection process and evaluate its efficiency based on the probability distribution used.

We propose a novel approach to determining the effectiveness of event detection systems, and evaluate the method presented here against this new ground truth.

Then, using a real credit card fraud dataset provided by a large European card processing company, we compare state-of-the-art credit card fraud detection models, and evaluate how the different sets of features have an impact on the results.

To compare detection rates and evaluate the clinical relevance of cytokeratin-19 (CK-19) mRNA-positive cells in the peripheral blood (circulating tumour cells, CTCs) and bone marrow (disseminated tumour cells; DTCs) of patients with early breast cancer.

We conducted repeated acoustic surveys to determine species presence/non-detection and evaluated a priori models relating detection probability and occupancy to site- and landscape-level metrics for 6 species/genera.

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