Bioengineering MDPI

💥Excited for the publication: "The Transformation Experiment of Frederick Griffith I: Its Narrowing and Potential for the Creation of Novel Microorganisms"
💡The construction of artificial microorganisms commonly relies on genome transfer between closely related species, limiting the diversity of synthetic biology approaches. This review revisits the historical foundations of bacterial transformation, from Frederick Griffith’s early experiments to modern genome-transfer strategies, arguing that inheritance extends beyond DNA alone. By considering structural and organizational cellular components alongside genetic information, the work explores broader possibilities for creating novel microbial systems.
🔗https://brnw.ch/21x2W3J
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💥Excited for the publication: "Benchmarking Interpretability in Healthcare Using Pattern Discovery and Disentanglement"
💡Artificial intelligence systems in healthcare often struggle with interpretability, limiting their adoption in clinical decision-making. This study benchmarks the Pattern Discovery and Disentanglement (PDD) framework, an unsupervised learning approach designed to generate interpretable clustering and knowledge representations from clinical notes and diagnostic codes. Compared with common post hoc interpretability methods such as SHAP and Integrated Gradients, the results suggest that globally interpretable approaches may better support clinicians in understanding AI-assisted diagnostic reasoning.
🔗https://brnw.ch/21x2USR
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💥Excited for the publication: "The Feasibility of RGB-D Gaze Intention Measurement in Children with Autism Using Azure Kinect"
💡Interpreting gaze is a key component of social interaction, yet accurately tracking gaze direction remains challenging, particularly in studies involving children with autism spectrum disorder. This study presents a gaze estimation approach using Azure Kinect to measure both gaze direction and head position with high accuracy. Applied to children with autism spectrum disorder, the system enables tracking of visual attention toward clinicians, supporting more precise assessment of social intent and interaction.
🔗https://brnw.ch/21x2UAj
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