Results 241 to 250 of about 23,771,265 (342)
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang +6 more
wiley +1 more source
External Validation of Potential Breath Biomarkers for Asthma: A Step Forward Toward the Clinical Implementation of Breath Analysis. [PDF]
Sola-Martínez RA +2 more
europepmc +1 more source
The study presents a low‐cost, noninvasive system for real‐time neonatal respiratory monitoring. A flexible, screen‐printed sensor patch captures chest movements with high sensitivity and minimal drift. Combined with machine learning, the system accurately detects breathing patterns and offers a practical solution for neonatal care in low‐resource ...
Gitansh Verma +3 more
wiley +1 more source
A Review of Trans‐Dimensional Kirigami: From Compliant Mechanism to Multifunctional Robot
This review outlines recent advancements in the geometric design and mechanical properties of kirigami. The kirigami is classified into two categories from a compliant mechanism perspective, highlighting their applications in metamaterials and robotic systems. Finally, the future research directions, is explored focusing on the potential of integrating
Yang Yu +14 more
wiley +1 more source
Breath Analysis: Identification of Potential Volatile Biomarkers for Non-Invasive Diagnosis of Chronic Kidney Disease (CKD). [PDF]
Di Gilio A +8 more
europepmc +1 more source
This study introduces a biomarker‐agnostic diagnostic strategy for ovarian cancer, utilizing a machine learning‐enhanced electronic nose to analyze volatile organic compound signatures from blood plasma. By overcoming the dependence on specific biomarkers, this approach enables accurate detection, staging, and cancer type differentiation, offering a ...
Ivan Shtepliuk +4 more
wiley +1 more source
AI Guided Protein Design for Next‐Generation Autogenic Engineered Living Materials
Autogenic engineered living materials (ELMs) integrate biology and materials science to create self‐regenerating and self‐healing materials. This perspective highlights emerging strategies in protein engineering and AI‐guided de novo design to expand the capabilities of autogenic ELMs.
Hoda M. Hammad, Anna M. Duraj‐Thatte
wiley +1 more source
Breath Analysis via Gas Chromatography-Mass Spectrometry (GC-MS) in Chronic Coronary Syndrome (CCS): A Proof-of-Concept Study. [PDF]
Lombardi M +10 more
europepmc +1 more source

