Bacterial Infection

Identification of Bacterial Pathogens at Genus and Species Levels through Combination of Raman Spectrometry and Deep-Learning Algorithms.

The rapid and accurate identification of the causing agents during bacterial infections would greatl...

Predicting risk of sepsis, comparison between machine learning methods: a case study of a Virginia hospital.

Sepsis is an inflammation caused by the body's systemic response to an infection. The infection coul...

Magnetic torque-driven living microrobots for increased tumor infiltration.

Biohybrid bacteria-based microrobots are increasingly recognized as promising externally controllabl...

Light-driven microrobots: capture and transport of bacteria and microparticles in a fluid medium.

The design of simple microrobotic systems with capabilities to address various applications like car...

Sentiment Classification of Chinese Tourism Reviews Based on ERNIE-Gram+GCN.

Nowadays, tourists increasingly prefer to check the reviews of attractions before traveling to decid...

Classification and Detection of COVID-19 and Other Chest-Related Diseases Using Transfer Learning.

COVID-19 has infected millions of people worldwide over the past few years. The main technique used ...

Nondestructive and multiplex differentiation of pathogenic microorganisms from spoilage microflora on seafood using paper chromogenic array and neural network.

Non-destructive detection of human foodborne pathogens is critical to ensuring food safety and publi...

De novo design of anti-tuberculosis agents using a structure-based deep learning method.

Mycobacterium tuberculosis (Mtb) is a pathogen of major concern due to its ability to withstand both...

Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery by Deep Learning-Based Medical Data Association Rules Method.

It is of great significance to explore the characteristic factors of postoperative nursing safety ev...

Label-free bacteria identification for clinical applications.

We have developed a system for bacteria identification based on absorption spectroscopy in the mid-i...

GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention.

Channel attention mechanisms have been commonly applied in many visual tasks for effective performan...

Machine learning for cell type classification from single nucleus RNA sequencing data.

With the advent of single cell/nucleus RNA sequencing (sc/snRNA-seq), the field of cell phenotyping ...

Interpretable deep learning of myelin histopathology in age-related cognitive impairment.

Age-related cognitive impairment is multifactorial, with numerous underlying and frequently co-morbi...

The hiatus between organism and machine evolution: Contrasting mixed microbial communities with robots.

Mixed microbial communities, usually composed of various bacterial and fungal species, are fundament...

Bacteria-inspired magnetically actuated rod-like soft robot in viscous fluids.

This paper seeks to design, develop, and explore the locomotive dynamics and morphological adaptabil...

MolPredictX: Online Biological Activity Predictions by Machine Learning Models.

Here we report the development of MolPredictX, an innovate and freely accessible web interface for b...

Deep Learning-Enabled Raman Spectroscopic Identification of Pathogen-Derived Extracellular Vesicles and the Biogenesis Process.

Pathogenic bacterial infections, exacerbated by increasing antimicrobial resistance, pose a major th...

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity.

Microorganisms growing in their habitat constitute a complex system. How the individual constituents...

Deep learning research should be encouraged for diagnosis and treatment of antibiotic resistance of microbial infections in treatment associated emergencies in hospitals.

Machine learning approach identifies prominent codons from different degenerate groups influencing gene expression in bacteria.

Unequal usage of synonymous codons is known as codon usage bias (CUB), which is generally different ...

PK-RNN-V E: A deep learning model approach to vancomycin therapeutic drug monitoring using electronic health record data.

Vancomycin is a commonly used antimicrobial in hospitals, and therapeutic drug monitoring (TDM) is r...