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 ...
The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...
Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...
Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
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 ...
Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...
A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...
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Machine learning could yield faster, cheaper lithium-ion battery development
Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could dramatically slash the cost and energy required to develop new lithium-ion ...
The question of whether prehospital emergency anaesthesia and intubation improves survival in patients with major trauma has ...
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