1don MSN
Limitations of AI-based material prediction: Crystallographic disorder represents a stumbling block
Computer simulations and artificial intelligence often make significant errors when predicting the properties of new, ...
In a recent study published in the journal Nature Methods, a group of researchers developed a novel method called Ribonucleic Acid (RNA) High-Order Folding Prediction Plus (RhoFold+). This deep ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Widespread machine learning methods behind ‘link prediction’ are performing very poorly, study shows
As you scroll through any social media feed, you are likely to be prompted to follow or friend another person, expanding your personal network and contributing to the growth of the app itself. The ...
AI models outperform traditional statistics in predicting post-complete cytoreduction outcomes in ovarian cancer patients. AI's diagnostic accuracy was high for predicting overall survival and no ...
Understanding and preventing drug side effects holds a profound influence on drug development and utilization, profoundly impacting patients’ physical and mental well-being. Traditional artificial ...
In the rapidly advancing field of computational biology, a newly peer-reviewed review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The ...
Data assimilation is an important mathematical discipline in earth sciences, particularly in numerical weather prediction (NWP). However, conventional data assimilation methods require significant ...
Precision medicine experts take into account several factors when developing appropriate treatments for diseases, including population risk or incidence, the underlying genetic cause and potential ...
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