As artificial intelligence continues to integrate into various aspects of our lives, the next frontier in AI technology is quickly ...

Background Patients with severe aortic stenosis (AS) are at high risk of mortality, regardless of symptom status. Despite ...

Overview:  AI is transforming every industry, making skills like machine learning, data science, and automation essential for ...

For decades, the process of drug discovery has been a prolonged, costly, and unpredictable endeavor — an effort that ...

Successful implementation requires modern healthcare infrastructure, including reliable electricity, high-speed internet ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

A NEWLY published retrospective study has shown that AI, particularly deep-learning algorithms, can significantly reduce the rate of misdiagnosis in paediatric elbow fractures. The study analysed 755 ...

People are feeding blood test results, doctor’s notes and surgical reports into ChatGPT and the like. Experts have some concerns. Credit...Ricardo Santos Supported by By Maggie Astor Mollie Kerr, a 26 ...

A new machine learning model developed by The George Institute for Global Health can successfully predict heart disease risk in women by analyzing mammograms. The findings were published today in ...

The recent surge in demand for timely and accurate health information has highlighted the need for more advanced data analysis tools. To reduce the incidence of preventable medical errors, ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...

Abstract: Distributed path planning for multiple unmanned aerial vehicles (UAVs) plays a significant role in data collection systems. However, insufficient collaboration among multiple UAVs and ...