In the past, plant breeding primarily involved the selection of plants with desirable characteristics through trial and error ...

To effectively present the uncertainty of convective-scale weather forecasts, convective-scale ensemble prediction systems ...

Current clinical tools rely on known cardiovascular risk elements, but they often do not account for complex interactions ...

Adolphi, C. and Sosonkina, M. (2025) Machine Learning and Simulation Techniques for Detecting Buoy Types from LiDAR Data.

One of the most agonizing experiences a cancer patient suffers is waiting without knowing: waiting for a diagnosis, waiting ...

While ML models are powerful tools for predicting diabetes, their lack of interpretability presents a major challenge for clinical adoption. Healthcare professionals require AI models to not only be ...

Neural networks can help to process large datasets and develop highly accurate decisions or predictions ... that use artificial neural networks and machine learning (ML) to function. One of the most ...

AI and ML technologies are increasingly deployed to enhance public safety by improving crime detection, predictive policing, ...

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Conclusions A fully automatic model for DTFA prediction was developed and validated. The presented method improved expert assessment of difficult ... to capture the most relevant anatomical features ...

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In a world with auto-correct, Google, and apps like Grammarly, spelling has become less important. Still, knowing the most difficult words to spell in English might come in handy. When writing a ...