AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Pollen

Showing 1 to 10 of 36 articles

Clear Filters

A deep learning LSTM-based approach for forecasting annual pollen curves: Olea and Urticaceae pollen types as a case study.

Computers in biology and medicine
Airborne pollen can trigger allergic rhinitis and other respiratory diseases in the synthesised population, which makes it one of the most relevant biological contaminants. Therefore, implementing accurate forecast systems is a priority for public he...

Pollen identification through convolutional neural networks: First application on a full fossil pollen sequence.

PloS one
The automation of pollen identification has seen vast improvements in the past years, with Convolutional Neural Networks coming out as the preferred tool to train models. Still, only a small portion of works published on the matter address the identi...

Harnessing artificial intelligence for analysing the impacts of nectar and pollen feeding in conservation biological control.

Current opinion in insect science
Plant-derived foods, such as nectar and pollen, have garnered substantial research attention due to their potential to support natural enemies of pests. This review is a pioneering exploration of the potential for artificial intelligence approaches t...

Local spatiotemporal dynamics of particulate matter and oak pollen measured by machine learning aided optical particle counters.

The Science of the total environment
Conventional techniques for monitoring pollen currently have significant limitations in terms of labour, cost and the spatiotemporal resolution that can be achieved. Pollen monitoring networks across the world are generally sparse and are not able to...

Identifying influence factors and thresholds of the next day's pollen concentration in different seasons using interpretable machine learning.

The Science of the total environment
The prevalence of pollen allergies is a pressing global issue, with projections suggesting that half of the world's population will be affected by 2050 according to the estimation of the World Health Organization (WHO). Accurately forecasting pollen ...

Improved Classification Performance of Bacteria in Interference Using Raman and Fourier-Transform Infrared Spectroscopy Combined with Machine Learning.

Molecules (Basel, Switzerland)
The rapid and sensitive detection of pathogenic and suspicious bioaerosols are essential for public health protection. The impact of pollen on the identification of bacterial species by Raman and Fourier-Transform Infrared (FTIR) spectra cannot be ov...

Estimation of the amount of pear pollen based on flowering stage detection using deep learning.

Scientific reports
Pear pollination is performed by artificial pollination because the pollination rate through insect pollination is not stable. Pollen must be collected to secure sufficient pollen for artificial pollination. However, recently, collecting sufficient a...

Spatiotemporal modelling of airborne birch and grass pollen concentration across Switzerland: A comparison of statistical, machine learning and ensemble methods.

Environmental research
BACKGROUND: Statistical and machine learning models are commonly used to estimate spatial and temporal variability in exposure to environmental stressors, supporting epidemiological studies. We aimed to compare the performances, strengths and limitat...

Imaging pollen using a Raspberry Pi and LED with deep learning.

The Science of the total environment
The production of low-cost, small footprint imaging sensor would be invaluable for airborne global monitoring of pollen, which could allow for mitigation of hay fever symptoms. We demonstrate the use of a white light LED (light emitting diode) to ill...

Modelling of pome fruit pollen performance using machine learning.

Scientific reports
Agriculture, particularly fruit production, is considered a crucial industry with a significant economic impact in many countries. Extreme fluctuations in air temperature can negatively affect the flowering periods of fruit species. Therefore, it is ...