Infectious Disease

Machine learning assisted masking of parasitic signals in Bragg coherent diffraction imaging.

Bragg coherent diffraction imaging (BCDI) is a lens-less technique capable of imaging the strain in a particle in the size range from 20 nm up to several micrometres. This indirect measurement technique, used in X-ray synchrotrons or free-electron lasers all over the world, requires an inversion step using iterative algorithms in order to recover the real-space complex object encoding the particle...

Development and validation of an interpretable machine learning model for early prediction of deterioration in patients with severe fever with thrombocytopenia syndrome.

BACKGROUND: Severe Fever with Thrombocytopenia Syndrome (SFTS) is a severe tick-borne viral infection with high mortality, making the timely prediction of clinical deterioration critical. Current predictive models lack timeliness and generalizability. Therefore, this study aimed to develop and validate an interpretable machine learning model for the early prediction of deterioration in SFTS patien...

Exploring variation in research priorities generated by AI tools.

BACKGROUND: Artificial intelligence (AI) tools based on large language models (LLMs) are being increasingly used by researchers and may play a role in...

How ready are we to use artificial intelligence in our fight against Antimicrobial resistance? An ESGAID and EAAS perspective.

INTRODUCTION: Antimicrobial resistance (AMR) remains one of the greatest threats to global health, requiring innovative approaches to antibiotic disco...

Reviewing the Artificial Intelligence Boost for Accelerating the Development of Novel Antimicrobial Peptides.

Antimicrobial resistance (AMR) is one of the most critical public health threats of the 21st century and is projected to become a leading cause of mor...

Gut microbiome signatures associated with depression and obesity.

UNLABELLED: Depression and obesity are highly comorbid and likely involve common risk factors and pathophysiological mechanisms, which could crosslink...

Machine Learning Algorithms to Predict Venous Thromboembolism in Patients With Sepsis in the Intensive Care Unit: Multicenter Retrospective Study.

BACKGROUND: Venous thromboembolism (VTE) is a common and severe complication in intensive care unit (ICU) patients with sepsis. Conventional risk stra...

Computational framework and machine learning approach to fractional order soil helminth infections disease model for control mechanism.

Soil-transmitted helminth (STH) infections are exceedingly common, estimated to afflict 1.5 billion individuals worldwide, or 24% of the total populat...

Leveraging universal and transfer learning models for influenza prediction in Thailand.

Influenza is a major respiratory disease that causes significant morbidity and mortality worldwide. Accurate predictions of influenza incidence enable...

Early prediction of colonization by carbapenemase-producing enterobacterales at ICU admission using machine learning.

Colonization by carbapenemase-producing Enterobacterales (CPE) on admission to an intensive care unit (ICU) poses a serious threat to infection contro...

Artificial Intelligence-Based Medical Devices for Diabetic Retinopathy Screening in the European Union.

BACKGROUND: Diabetic retinopathy (DR) remains a leading cause of preventable blindness, yet screening programs across Europe face persistent workforce...

IL2Pepscan: a machine learning framework for predicting IL-2 inducing peptides and their identification across global viral proteomes.

Interleukin-2 (IL-2) is a pivotal cytokine involved in regulating immune responses, particularly in the activation and proliferation of T cells. Inter...

Predicting antimicrobial resistance in Staphylococcus aureus using machine learning: Insights from a five-year surveillance study.

Staphylococcus aureus is a leading cause of both community- and hospital-acquired infections, and the growing prevalence of antimicrobial resistance c...

Highly efficient and durable Th1-biased protective immunity from a novel mRNA vaccine against RSV via AI-assisted antigen screening.

Respiratory syncytial virus (RSV) is a leading cause of severe respiratory illness, imposing a significant burden on global health and society. Here, ...

Microvascular inflammation in the kidney transplant, beyond acute antibody-mediated rejection.

PURPOSE OF REVIEW: Microvascular inflammation (MVI) is a central feature of allograft rejection, traditionally associated with antibody-mediated rejec...

Agri-vision Bangladesh: A multi-crop augmented image dataset for automated disease diagnosis in Bottle Gourd, Zucchini, Papaya, and Tomato.

This article introduces Agri-Vision Bangladesh, a comprehensive, augmented image dataset designed to advance automated disease diagnosis in four econo...

Machine learning models for early mortality prediction in severe fever with thrombocytopenia syndrome.

Severe fever with thrombocytopenia syndrome (SFTS) is a high-fatality viral disease where early mortality risk prediction is vital for clinical manage...

Identification of the biomarkers associated with lipid metabolism and endoplasmic reticulum stress in pediatric sepsis through bioinformatics analysis and quantitative reverse transcriptase PCR (qRT-PCR) assay.

BACKGROUND: Sepsis constitutes a critical clinical condition characterized by organ failure and systemic inflammation, especially affecting children. ...

From inhibition to regulation: serpins in health and disease.

This issue of the Biomedical Journal highlights regulatory mechanisms that shape aging, disease progression, and biological complexity across molecula...

Rapid Detection of NDM-Producing Carbapenem-Resistant Escherichia coli Using MALDI-TOF MS Combined with Machine Learning Techniques.

BACKGROUND: Carbapenem-resistant Escherichia coli (CREC) producing New Delhi metallo-beta-lactamase (NDM) poses a substantial threat to global public ...