Journal of Biostatistics and Biometric Applications

About

About the Journal

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.

Why publish with us

Built for researchers

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Fast peer review

Target first decision within 21 days. Double-blind review by 2-3 field experts.

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Fully open access

All articles CC BY 4.0. No paywalls. Compliant with funder mandates worldwide.

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DOI & indexing

Every article receives a unique DOI. Indexed in PubMed, Google Scholar, CrossRef.

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Rapid publication

Published within 7 days of acceptance. No unnecessary delays in dissemination.

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Global & equitable

Readers in 170+ countries. Waiver program available for authors from developing nations.

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No content limits

No word limits. Multiple article formats: research, reviews, case reports, short communications.

How it works

Simple. Transparent. Streamlined.

Submit

Upload your manuscript via our online portal. Quality check within 48 hours.

Review

Double-blind peer review by 2-3 field experts. Target decision: ~21 days.

Revise

Constructive feedback from reviewers. Dedicated editorial support throughout.

Publish

Published within 7 days. DOI assigned via CrossRef. Globally indexed.

Submit Manuscript →

Highlights

Research Highlights

Classifying Stress from Heart Rate Variability Using Salivary Biomarkers as Reference.

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 Directional Number Transitional Graph for Dynamic Texture Recognition

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.

Learning Compact Binary Face Descriptor for Face Recognition.

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

An Effective and Novel Neural Network Ensemble for Shift Pattern Detection in Control Charts.

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.