For decades, knowing what lies beneath a farmer’s feet has meant one thing: bagging up soil, sending it to a laboratory, and ...

Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS for HSIs remains ...

An automated machine-learning program developed by researchers from Edith Cowan University (ECU) in conjunction with the University of Manitoba has been able to identify potential cardiovascular ...

Medicare's six-year WISeR programme uses AI and machine learning to assist reviews of selected services in six states, with ...

Smartwatches are among the wearable devices that gather health data. Translating that data into useful information can be complicated and expensive. (iStock) The human body constantly generates a ...

The current MA risk adjustment model has shortcomings, both in predictive accuracy and payment equity across the Medicare program, which could be mitigated using lessons from machine learning. MA ...

Every time a mosquito takes a blood meal, it leaves behind a molecular record of the animal it fed on. Decoding that record has long been one of the most laborious tasks in vector biology, yet it is ...

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...

Salty soils are causing reduced crop density, lower yields and barren lands unable to sustain crop growth. Sea level rise, intense storm surges and the overextraction of groundwater are driving this ...

The changing use of the word algorithm reflects this enhanced visibility. In fact, the meaning of this word has changed ...