Infectious Disease

Bacterial Infection

Latest AI and machine learning research in bacterial infection for healthcare professionals.

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Scalable de novo classification of antibiotic resistance of Mycobacterium tuberculosis.

MOTIVATION: World Health Organization estimates that there were over 10 million cases of tuberculosi...

Jun 2024 38940175
A compact model of Escherichia coli core and biosynthetic metabolism

Metabolic models condense biochemical knowledge about organisms in a structured and standardised w...

Computing Optimal Manipulations in Cryptographic Self-Selection Proof-of-Stake Protocols

Cryptographic Self-Selection is a paradigm employed by modern Proof-of-Stake consensus protocols t...

PathoLM: Identifying pathogenicity from the DNA sequence through the Genome Foundation Model

Pathogen identification is pivotal in diagnosing, treating, and preventing diseases, crucial for c...

skandiver: a divergence-based analysis tool for identifying intercellular mobile genetic elements

Mobile genetic elements (MGEs) are as ubiquitous in nature as they are varied in type, ranging fro...

Bipartite Matching in Massive Graphs: A Tight Analysis of EDCS

Maximum matching is one of the most fundamental combinatorial optimization problems with applicati...

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding ge...

May 2024 39007592
Machine Learning for Clinical Decision Support of Acute Streptococcal Pharyngitis: A Pilot Study.

BACKGROUND: Group A Streptococcus (GAS) is the predominant bacterial pathogen of pharyngitis in chil...

May 2024 38736345
Machine learning reveals ferroptosis features and a novel ferroptosis classifier in patients with sepsis.

OBJECTIVE: Sepsis is an organ malfunction disease that may become fatal and is commonly accompanied ...

May 2024 38780016
A microbial knowledge graph-based deep learning model for predicting candidate microbes for target hosts.

Predicting interactions between microbes and hosts plays critical roles in microbiome population gen...

Mar 2024 38555472
Understanding gut microbiome-based machine learning platforms: A review on therapeutic approaches using deep learning.

Human beings possess trillions of microbial cells in a symbiotic relationship. This relationship ben...

Mar 2024 38491814
Coracle-a machine learning framework to identify bacteria associated with continuous variables.

SUMMARY: We present Coracle, an artificial intelligence (AI) framework that can identify association...

Jan 2024 38123508
Enhancing Antibiotic Stewardship: A Machine Learning Approach to Predicting Antibiotic Resistance in Inpatient Care.

Antibiotics have been crucial in advancing medical treatments, but the growing threat of antibiotic ...

Jan 2024 40417584
[Research progress of artificial intelligence technology in early diagnosis of sepsis].

Sepsis is caused by infection, which can ultimately lead to multiple organ dysfunction and even life...

Jan 2024 38404282
Machine learning-based antibiotic resistance prediction models: An updated systematic review and meta-analysis.

BACKGROUND: The widespread use of antibiotics has led to a gradual adaptation of bacteria to these d...

Jan 2024 38875058
Diagnostic performance of machine-learning algorithms for sepsis prediction: An updated meta-analysis.

BACKGROUND: Early identification of sepsis has been shown to significantly improve patient prognosis...

Jan 2024 38968031
Data-Driven Clinical Pharmacy Research: Utilizing Machine Learning and Medical Big Data.

To conduct clinical pharmacy research, we often face the limitations of conventional statistical met...

Jan 2024 39358238
Prediction of Vancomycin-Associated Nephrotoxicity Based on the Area under the Concentration-Time Curve of Vancomycin: A Machine Learning Analysis.

Several machine learning models have been proposed to predict vancomycin (VCM)-associated nephrotoxi...

Jan 2024 39603615
A Study on Machine Learning Models in Detecting Cognitive Impairments in Alzheimer's Patients Using Cerebrospinal Fluid Biomarkers.

Several research studies have demonstrated the potential use of cerebrospinal fluid biomarkers such ...

Jan 2024 39657974
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