Infectious Disease

Latest AI and machine learning research in infectious disease for healthcare professionals.

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Rapid and accurate identification of foodborne bacteria: a combined approach using confocal Raman micro-spectroscopy and explainable machine learning.

This study proposes a rapid identification method for foodborne pathogens by combining Raman spectro...

Deep learning in the discovery of antiviral peptides and peptidomimetics: databases and prediction tools.

Antiviral peptides (AVPs) represent a novel and promising therapeutic alternative to conventional an...

Unveiling drug-induced osteotoxicity: A machine learning approach and webserver.

Drug-induced osteotoxicity refers to the harmful effects certain pharmaceuticals have on the skeleta...

Prediction and Prioritisation of Novel Anthelmintic Candidates from Public Databases Using Deep Learning and Available Bioactivity Data Sets.

The control of socioeconomically important parasitic roundworms (nematodes) of animals has become ch...

Fine-tuned deep learning models for early detection and classification of kidney conditions in CT imaging.

The kidney plays a vital role in maintaining homeostasis, but lifestyle factors and diseases can lea...

Colonial bacterial memetic algorithm and its application on a darts playing robot.

In this paper, we present the Colonial Bacterial Memetic Algorithm (CBMA), an advanced evolutionary ...

An ensemble approach improves the prediction of the COVID-19 pandemic in South Korea.

BACKGROUND: Modelling can contribute to disease prevention and control strategies. Accurate predicti...

Systematic review of infodemiology studies using artificial intelligence: social media posts on HIV preexposure prophylaxis.

OBJECTIVES: To explore how artificial intelligence (AI) can enhance infodemiology, which distributes...

Role of eccentricity based topological descriptors to predict anti-HIV drugs attributes with supervised machine learning algorithms.

Chemical graphs are mathematical representations of molecular structures, where atoms are represente...

Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study.

BACKGROUND: Pertussis is a highly contagious respiratory disease. Even though vaccination has reduce...

Constructing an early warning model for elderly sepsis patients based on machine learning.

Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is ne...

Large Language Model-Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study.

BACKGROUND: Sepsis is a complex, life-threatening condition characterized by significant heterogenei...

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mor...

Machine Learning-Guided Screening and Molecular Docking for Proposing Naturally Derived Drug Candidates Against MERS-CoV 3CL Protease.

In this study, we utilized machine learning techniques to identify potential inhibitors of the MERS-...

Explainable AI for Symptom-Based Detection of Monkeypox: a machine learning approach.

BACKGROUND: Monkeypox, a viral zoonotic disease, is an emerging global health concern, with rising i...

Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.

OBJECTIVE: Bloodstream infection (BSI) is a significant cause of mortality in patients with hematolo...

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