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Infection control / Modes of transmission

Latest AI and machine learning research in infection control / modes of transmission for healthcare professionals.

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Showing 1781-1800 of 5,474 articles

Organization of mouse prefrontal cortex subnetwork revealed by spatial single-cell multi-omic analysis of SPIDER-Seq

Deciphering the connectome, anatomy, transcriptome and spatial-omics integrated multi-modal brain atlas and the underlying organization principles remains a great challenge. We developed a Single-cell Projectome-transcriptome In situ Deciphering Sequencing (SPIDER-Seq) technique by combining viral barcoding tracing with single-cell sequencing and spatial-omics. This empowers us to delineate a inte...

Airborne Nanoplastics Perturb Mitochondrial Complex I via the ND6 Axis: Polymer-Specific Mitoepigenetic Remodeling Integrating Experimental, In Silico, and Machine Learning Analyses

Airborne nanoplastics constitute an emerging class of environmental contaminants, but their mitoepigenetic effects on human immune cells have not been systematically investigated. Ex vivo human lymphocytes were used to investigate integrated mitochondrial, epigenetic, and inflammatory responses induced by polystyrene (PS), polypropylene (PP), and polyvinyl chloride (PVC) nanoplastics. Fluorescence...

Forecasting invasive mosquito abundance in the Basque Country, Spain using machine learning techniques

Mosquito-borne diseases cause millions of deaths each year and are increasingly spreading from tropical and subtropical regions into temperate zones, ...

Non-Contact Optical Blood Pressure Biometry Using AI-Based Analysis of Non-Mydriatic Fundus Imaging

This study was developed to determine whether a machine learning model could be developed to assess blood pressure with accuracy comparable to arm cuf...

Trust in large language model-based solutions in healthcare among people with and without diabetes: a cross-sectional survey from the Health in Central Denmark cohort

Large language models have gained significant public awareness since ChatGPT’s release in 2022. This study describes the perception of chatbot-assiste...

Identifying and Forecasting Importation and Asymptomatic Spreaders of Multi-drug Resistant Organisms in Hospital Settings

Healthcare-associated infections (HAIs) from multi-drug resistant organisms (MDROs) pose a signif-icant challenge for healthcare systems. Patients can...

Using Artificial Intelligence to Personalize Caring Contact Messages for Recently Discharged Patients: Protocol for a Mixed-Methods Feasibility Study

Suicide risk is substantially elevated following discharge from a psychiatric hospitalization. Caring Contact (CC) messages are brief messages of hope...

The epidemiology of pathogens with pandemic potential: A review of key parameters and clustering analysis

In the light of the COVID-19 pandemic many countries are trying to widen their pandemic planning from its traditional focus on influenza. However, it ...

DoBSeqWF: A framework for sensitive detection of individual genetic variation in pooled sequencing data

Population screening for rare genetic diseases is limited by the high cost of next- generation sequencing. Double-batched sequencing (DoBSeq) is a cos...

Estimating the worst-case scenario for malaria parasite rate in sub-Saharan Africa

Malaria remains a leading cause of morbidity and mortality worldwide, with sub-Saharan Africa bearing the highest burden. Stalled progress under an in...

Reinforcement learning-based control of epidemics on networks of communities and correctional facilities

Correctional facilities can act as amplifiers of infectious disease outbreaks. Small community outbreaks can cause larger prison outbreaks, which can ...

Activation status of immune cells in the airway is a defining feature of severe fungal asthma

Airborne fungi are potent inducers of respiratory disease and cause the debilitating conditions severe asthma with fungal sensitisation (SAFS) and all...

From subthalamic local field potentials to the selection of chronic deep brain stimulation contacts in Parkinson’s disease - A systematic review

Programming deep brain stimulation (DBS) of the subthalamic nucleus for optimal symptom control in Parkinson’s Disease (PD) requires time and trained ...

STM-GNN: Space-Time-and-Memory Graph Neural Networks for Predicting Multi-Drug Resistance Risks in Dynamic Patient Networks

Hospital-acquired infections (HAIs), particularly those caused by multidrug-resistant (MDR) bacteria, pose significant risks to vulnerable patients. A...

Dense sampling of choices links high learning rates to obesity and low reward sensitivity to binge eating

Mounting evidence shows that obesity is associated with alterations in dopamine transmission. However, in humans, corresponding changes in dopamine-de...

Dengue forecasting and outbreak detection in Brazil using LSTM: integrating human mobility and climate factors

Dengue fever is a major global health concern, with Brazil experiencing recurrent and severe outbreaks due to its favorable climate factors, socio-env...

Patient-Specific and Interpretable Deep Brain Stimulation Optimisation Using MRI and Clinical Review Data

Optimisation of Deep Brain Stimulation (DBS) settings is a key aspect in achieving clinical efficacy in movement disorders, such as the Parkinson’s di...

Associations Between Meteorological Factors and Influenza A/B Incidence in Subtropical China: A Six-Year Surveillance Study with Deep Learning Modelling for Influenza Early Warning

Influenza burden in subtropical regions like southeastern China is shaped by meteorological factors-driven complex transmission patterns that differ f...

A Web-Based Application for Real-Time Malaria Prediction using Environmental Variables

Malaria remains a persistent public health challenge in Zimbabwe, particularly in rural districts such as Mudzi in Mashonaland East Province, where se...

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