By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...
Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
ADM, Evolving Systems’ big data platform, securely stores and analyzes massive telecom data, from billing to network reports, ...
Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron ...
The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...
Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...
Artificial intelligence has taken the world by storm. In biology, AI tools called deep neural networks (DNNs) have proven invaluable for predicting the results of genomic experiments. Their usefulness ...
A machine-learning loop searched 14 million battery cathode compositions and found fivefold performance gains across four metrics using fewer than 200 experiments.
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