NTN applies AI and machine learning to accelerate bearing design, cut analysis time and reduce engineering workload.
Prospective data from over 100,000 participants in the Women’s Health Initiative show that the risk of ischemic colitis (IC) ...
Spinal metastasis, the spread of cancer to the spine, is a frequent complication in advanced cancer. It often causes severe ...
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New prognostic model improves survival prediction for spinal metastasis patients
Spinal metastasis, the spread of cancer to the spine, is a frequent complication in advanced cancer. It often causes severe ...
Spinal metastasis, the spread of cancer to the spine, is a frequent complication in advanced cancer. It often causes severe pain and paralysis ...
Vertical transfer students remain unguided in how best to achieve the degree outcomes they seek. There are better approaches, including a Transfer Scorecard.
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
This study investigated the dynamics of human cortical network activity with functional magnetic resonance imaging during movie watching and studied the modulation of these dynamics by subcortical ...
Machine learning added to NTN’s ABICS system reduces simulation time by more than 90 percent and automates dimension optimization for third-generation hub bearings, the company says.
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Soccer doesn't seem like an ideal setting for a workplace comedy. Yet, producer Bill Lawrence managed to make the pitch perfect in the profoundly satisfying "Ted Lasso." Spanning three seasons — at ...
Ted Lasso became one of the biggest shows on television in recent years, with its third season initially thought to be the final one. The Emmy Award-winning comedy, led by Jason Sudeikis, concluded ...
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