AIMC Topic: Lyme Disease

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Identification of potential biomarkers for Lyme disease using bioinformatics and machine learning.

Clinical and experimental medicine
Lyme disease (LD) presents significant diagnostic challenges due to the absence of a reliable screening method for initial detection. This study aimed to identify potential biomarkers using bioinformatics and machine learning algorithms, which may co...

Variables for habitat and vertebrate hosts of Ixodes scapularis are the best ecological predictors of the spatial spread of Lyme disease in the United States (2010-2019).

Parasites & vectors
BACKGROUND: Lyme disease (LD) is a major public health concern in North America. The incidence of LD has increased in part due to the rapid expansion of Ixodes scapularis infected with Borrelia burgdorferi sensu lato (Bb), the causative agent of LD. ...

The multiplexed single-tier InBios Lyme Detect Multiplex ELISA is more sensitive than standard two-tier tests in the early stages of Lyme disease.

Journal of clinical microbiology
UNLABELLED: There are nearly 500,000 cases of Lyme disease each year in the United States; 10%-20% of them result in the development of a debilitating chronic disease known as post-treatment Lyme disease. Existing standardized and modified two-tier t...

The potential to improve Lyme disease diagnostics through quantification of immunoglobulin class switching patterns.

Journal of clinical microbiology
N. Nair, A. Marques , E. J. Horn, G. Brown et al., J Clin Microbiol 63:e0034725, 2025, https://doi.org/10.1128/jcm.00347-25 present data to demonstrate that infection by , the primary causative agent of Lyme disease in the USA, leads to immunoglobuli...

A machine learning framework for estimating the probability of blacklegged tick population establishment in eastern Canada using Earth observation data.

PloS one
Ixodes scapularis ticks are the primary vector of Lyme disease (LD) in North America, and their range has expanded into southeastern and southcentral Canada with climate change. This study presents a comprehensive machine learning (ML) framework to e...

Automated tick classification using deep learning and its associated challenges in citizen science.

Scientific reports
Lyme borreliosis and tick-borne encephalitis significantly impact public health in Europe, transmitted primarily by endemic tick species. The recent introduction of exotic tick species into northern Europe via migratory birds, imported animals, and t...

Serologic biomarker discovery for differentiating Lyme disease from diseases with similar clinical symptoms using broad profiling of antibody binding.

Frontiers in immunology
INTRODUCTION: Lyme disease (LD) is a tick-borne disease that is a substantial public health burden with estimated about 0.5 million new cases per year in the US and increasing incidence. Differentiating Lyme disease, especially in its early stages, f...

Of Lyme disease and machine learning in a One Health world.

American journal of veterinary research
OBJECTIVE: Lyme disease is a vector-borne emerging zoonosis in Ontario driven by human population growth and climate change. Lyme disease is also a prime example of the One Health concept. While little can be done to immediately reverse climate chang...

Expert opinion elicitation for assisting deep learning based Lyme disease classifier with patient data.

International journal of medical informatics
BACKGROUND: Diagnosing erythema migrans (EM) skin lesion, the most common early symptom of Lyme disease, using deep learning techniques can be effective to prevent long-term complications. Existing works on deep learning based EM recognition only uti...

Long COVID diagnostic with differentiation from chronic lyme disease using machine learning and cytokine hubs.

Scientific reports
The absence of a long COVID (LC) or post-acute sequelae of COVID-19 (PASC) diagnostic has profound implications for research and potential therapeutics given the lack of specificity with symptom-based identification of LC and the overlap of symptoms ...