Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

• A new AI machine learning algorithm capable of predicting planetary orbits that may one day help accelerate physics research in other areas such as renewable energy. • Strikingly, the algorithms ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Tree-based ensemble models often outperform more complex deep learning architectures when applied to structured, tabular IoT data. While neural networks excel with image and unstructured inputs, ...

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account the laws of physics—using Newton's third law. Their research is published ...