Bioengineering, Free Full-Text

Perceptual and statistical evidence has highlighted voice characteristics of individuals affected by genetic syndromes that differ from those of normophonic subjects. In this paper, we propose a procedure for systematically collecting such pathological voices and developing AI-based automated tools to support differential diagnosis. Guidelines on the most appropriate recording devices, vocal tasks, and acoustical parameters are provided to simplify, speed up, and make the whole procedure homogeneous and reproducible. The proposed procedure was applied to a group of 56 subjects affected by Costello syndrome (CS), Down syndrome (DS), Noonan syndrome (NS), and Smith–Magenis syndrome (SMS). The entire database was divided into three groups: pediatric subjects (PS; individuals < 12 years of age), female adults (FA), and male adults (MA). In line with the literature results, the Kruskal–Wallis test and post hoc analysis with Dunn–Bonferroni test revealed several significant differences in the acoustical features not only between healthy subjects and patients but also between syndromes within the PS, FA, and MA groups. Machine learning provided a k-nearest-neighbor classifier with 86% accuracy for the PS group, a support vector machine (SVM) model with 77% accuracy for the FA group, and an SVM model with 84% accuracy for the MA group. These preliminary results suggest that the proposed method based on acoustical analysis and AI could be useful for an effective, non-invasive automatic characterization of genetic syndromes. In addition, clinicians could benefit in the case of genetic syndromes that are extremely rare or present multiple variants and facial phenotypes.

Continuous Cell-Free Replication and Evolution of Artificial Genomic DNA in a Compartmentalized Gene Expression System

Biomedical Engineering / Biomedizinische Technik

Biotechnology & Bioengineering, Biotechnology Journal

Bioengineering Vector Icon Symbol. Creative Sign from Biotechnology Icons Collection. Filled Flat Bioengineering Icon Stock Vector - Illustration of equipment, genetic: 150660001

What Is Bioengineering? - ASME

Frontiers Biological Materials: The Next Frontier for Cell-Free Synthetic Biology

PDF) ACID: a free tool for drug repurposing using consensus inverse docking strategy

CMBE journal (@CMBEjournal) / X

Biomedical Engineer Cover Letter Example (Free Guide)