<div style="text-align: justify; "><b><span style="font-size: 1rem;">A team of researchers from the Australian National University (ANU) has developed an artificial intelligence (AI) tool to more quickly and accurately classify brain tumors.</span><br></b></div><div style="text-align: justify;"><br></div><div style="text-align: justify;">In a study published on Friday, the team demonstrated that their deep learning model - DEPLOY - can accurately classify brain tumors into 10 major subtypes.</div><div style="text-align: justify;"><br></div><div style="text-align: justify;">The AI tool analyzes microscopic pictures of a patient's brain tissue to make its classification.</div><div style="text-align: justify;"><br></div><div style="text-align: justify;">Danh-Tai Hoang, the co-lead of the project from the Biological Data Science Institute at ANU, said that the current gold standard for diagnosing and categorizing brain tumors - a process called DNA methylation-based profiling - can take several weeks and is not widely available.</div><div style="text-align: justify;"><br></div><div style="text-align: justify;">By comparison, the AI tool can deliver results within hours.</div><div style="text-align: justify;"><br></div><div style="text-align: justify;">"Remarkably, DEPLOY achieved an unprecedented accuracy of 95 percent," Hoang said in a media release.</div><div style="text-align: justify;"><br></div><div style="text-align: justify;">"Furthermore, when given a subset of 309 particularly difficult to classify samples, DEPLOY was able to provide a diagnosis that was more clinically relevant than what was initially provided by pathologists."</div><div style="text-align: justify;"><br></div><div style="text-align: justify;">DEPLOY was trained and validated on a dataset of approximately 4,000 patients from the United States and Europe.</div><div style="text-align: justify;"><br></div><div style="text-align: justify;">Hoang said it could be used in the future to add to a pathologist's initial diagnosis or even prompt a re-evaluation when it finds disparities.</div><div style="text-align: justify;"><br></div><div style="text-align: justify;">The researchers believe it could eventually be used to help classify other types of cancer. - XINHUA</div><div style="text-align: justify;"><br></div><div style="text-align: justify; ">bnbd/fas</div>