- Predictors of Obstructive Sleep Apnea Risk among Blacks with Metabolic Syndrome
- Objectively Coding Intervention Fidelity During A Phone-Based Obesity Prevention Study
- Wake-up Strokes Are Similar to Known-Onset Morning Strokes in Severity and Outcome
- Acculturation and Subclinical Atherosclerosis among U.S. South Asians: Findings from the MASALA study
- Molecular Mechanism Linking BRCA1 Dysfunction to High Grade Serous Epithelial Ovarian Cancers with Peritoneal Permeability and Ascites
An accurate and noninvasive stress assessment from human physiology is a strenuous task. In this paper, a pattern recognition system to learn complex correlates between heart rate variability (HRV) features and salivary stress biomarkers is proposed.
Spatiotemporal image descriptors are gaining attention in the image research community for better representation of dynamic textures, A dynamic-micro-texture descriptor, i.e., spatiotemporal directional number transitional graph which describes both the spatial structure and motion of each local neighborhood by capturing the direction of natural flow in the temporal domain.
A compact binary face descriptor (CBFD) feature learning method for face representation and recognition. Given each face image, we first extract pixel difference vectors (PDVs) in local patches by computing the difference between each pixel and its neighboring pixels.
GIAO C-H COSY simulations merged with artificial neural networks pattern recognition analysis. Pushing the structural validation a step forward.
The structural validation problem using quantum chemistry approaches (confirm or reject a candidate structure) has been tackled with artificial neural network (ANN)-mediated multidimensional pattern recognition from experimental and calculated 2D C-H COSY
Pattern recognition in control charts is critical to make a balance between discovering faults as early as possible and reducing the number of false alarms. This work is devoted to designing a multistage neural network ensemble that achieves this balance which reduces rework and scrape without reducing productivity.
Journal of Biostatistics and Biometric Applications
Journal of Biostatistics and Biometric Applications (JBBA) is an open access journal which focuses on new trends in Biostatistics and Biometrics by rapidly publishing high-level peer-reviewed articles ranging from basic fundamental areas that deal with biological measurements research to statistical and mathematical methods applicable to data analysis, human clinical trials evaluation, recognition of individuals, etc.
Online Submission SystemJournal of Biostatistics and Biometric Applications is using online manuscript submission, review and tracking systems for quality and quick review processing. Review processing is performed by the editorial board members of Journal of Biostatistics and Biometric Applications or outside experts; at least two independent reviewer's approval followed by editor approval is required for acceptance of any citable manuscript.