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We recently developed a novel machine learning technique, the robust support vector machine (rSVM), that can achieve highly accurate classification in the face of data uncertainty from noise in training data, ubiquitous in clinical research.[1] Methods: We used the rSVM to classify participants as having manifest/nonmanifest HD based on UHDRS motor subscores, with observerrated DCL classifications forming the reference standard

Thus, while we interpret the findings in terms of D and B 12 , one should be cautious that the true causal factor might be a combination (e.g., overall micronutrient sufficiency) rather than these vitamins in isolation

Advancements in the biopharmaceutical industry have resulted in the development of several new protein and peptide based therapeutics

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