Infectious Disease

Construction and validation of HBV-ACLF bacterial infection diagnosis model based on machine learning.

OBJECTIVE: To develop and validate a novel diagnostic model for detecting bacterial infections in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) using advanced machine learning algorithms. The focus is on improving early clinical identification and interpretability.

Forecasting tuberculosis in Ethiopia using deep learning: progress toward sustainable development goal evidence from global burden of disease 1990-2021.

BACKGROUND: Tuberculosis (TB) is a preventable and treatable disease caused by Mycobacterium tuberculosis, which most often affects lungs and remains the second leading cause of death from infectious diseases worldwide. The National End TB Strategy aims to eliminate the TB epidemic by reducing TB-related deaths by 95% and decreasing incident TB cases by 90% by 2030, using 2015 as the baseline. Tub...

Automatic recognition and differentiation of pulmonary contusion and bacterial pneumonia based on deep learning and radiomics.

BACKGROUND: In clinical work, there are difficulties in distinguishing pulmonary contusion(PC) from bacterial pneumonia(BP) on CT images by the naked ...

Mortality predicting models for patients with infective endocarditis: a machine learning approach.

BACKGROUND: Infective endocarditis (IE) is a fatal cardiovascular disease with varied clinical manifestations but rapid progression. A series of exist...

AmpHGT: expanding prediction of antimicrobial activity in peptides containing non-canonical amino acids using multi-view constrained heterogeneous graph transformer.

BACKGROUND: Antimicrobial peptide (AMP) prediction has been extensively studied in recent years. However, many existing models do not fully leverage t...

AI-Accelerated Identification of Novel Antimicrobial Peptides for Inhibiting .

Fusarium head blight caused by threatens global wheat production, causing substantial yield reduction and mycotoxin accumulation. This study harnesse...

Multiomics and Machine Learning Identify Immunometabolic Biomarkers for Active Tuberculosis Diagnosis Against Nontuberculous Mycobacteria and Latent Tuberculosis Infection.

This study utilized multiomics combined with a comprehensive machine learning-based predictive modeling approach to identify, validate, and prioritize...

Python-driven impedance profiling on peptide-functionalized biosensor for detection of HIV gp41 envelope protein.

UNLABELLED: This study presents the first label-free impedimetric biosensor for the detection of HIV envelope protein gp41 using antimicrobial peptide...

Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensembles.

Once deployed, medical image analysis methods are often faced with unexpected image corruptions and noise perturbations. These unknown covariate shift...

Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications.

BACKGROUND: The application of artificial intelligence (AI) in medicine has garnered significant attention in recent years, offering new possibilities...

Identification of key genes and development of an identifying machine learning model for sepsis.

OBJECTIVE AND DESIGN: This study aims to identify key genes of sepsis and construct a model for sepsis identification through integrated multi-organ s...

Antimicrobial peptides: An important link in the game theory between plants and pathogens.

BACKGROUND: Antimicrobial peptides (AMPs) are peptides produced by organisms during the evolutionary process to defend themselves against external bio...

Discovery of SARS-CoV-2 papain-like protease inhibitors through machine learning and molecular simulation approaches.

The papain-like protease (PLpro), a cysteine protease found in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), plays a crucial role in v...

AntiBMPNN: Structure-Guided Graph Neural Networks for Precision Antibody Engineering.

Antibodies are crucial for medical applications, yet traditional methods for designing sequences are inefficient. This study introduces AntiBMPNN, an ...

Development and Validation of a Hierarchical Machine Learning Method using MALDI-TOF Mass Spectrometry for Rapid SCCmec Typing and PVL Detection in MRSA: A Multi-Center Study.

OBJECTIVES: Methicillin-resistant (MRSA) is a major public health concern because of its genotypic diversity and association with severe infections, ...

HEalth Record Optimization for Identifying Candidates for HIV PRe-Exposure Prophylaxis: A Community-Informed Approach to Model Development.

Electronic health record (EHR)-based models to identify individuals who may benefit from pre-exposure prophylaxis (PrEP) outperform traditional risk s...

[Early warning scores: a rapid umbrella review].

BACKGROUND: Early warning scores (EWS) are used for monitoring and evaluating vital signs in hospitalized patients. With EWS, escalating measures for ...

ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China: Time Series Analysis.

BACKGROUND: Influenza in mainland China results in a large number of outpatient and emergency visits related to influenza-like illness (ILI) annually....

Walking Backward to Ensure Risk Management of Large Language Models in Medicine.

This paper examines in what way providers of specialized Large Language Models (LLM) pre-trained and/or fine-tuned on medical data, conduct risk manag...

A dataset of microscopic spirometra mansoni for medical image segmentation.

Accurate diagnosis of adult Spirometra mansoni infections remains challenging, due to the limited sensitivity and high cost associated with immunodiag...