The team say this new approach could reduce the need for invasive and costly diagnostic tests while improving treatment outcomes early when interventions such as lifestyle changes or new medicines may have a chance to work best.
The teams from the Universities of East Anglia (UEA), Sheffield and Leeds created an intelligent computer model that utilises AI to examine heart images from MRI scans in a specific view known as the four-chamber plane.
The national study asked children and young people aged six to 23 years old, across all four UK nations for their views on how they would like AI to be used to enhance their healthcare.
Until now, that is.
The research team behind the study published on Wednesday, July 3, in the journal PLOS ONE, took on the serious task of comparing participants’ reactions to jokes written by ChatGPT 3.5 and others written by people.
Researchers from the Wellcome Sanger Institute, University of the Witwatersrand and National Institute for Communicable Diseases in South Africa, the University of Cambridge, and partners across the Global Pneumococcal Sequencing project, integrated genomic data from nearly 7,000 Streptococcus pneumoniae (pneumococcus) samples collected in South Africa with detailed human mobility data.
DeepPT, developed in collaboration with scientists at the National Cancer Institute in America and pharmaceutical company Pangea Biomed, works by predicting a patient's messenger RNA (mRNA) profile.
Tulane University researchers made progress toward that vision by developing a new deep learning algorithm that outperformed existing computer-based osteoporosis risk prediction methods, potentially leading to earlier diagnoses and better outcomes for patients with osteoporosis risk.