Tag: Early detection

Nigeria has a high hepatitis B virus (HBV) prevalence rate of 9.5%. To combat this issue, researchers have developed an affordable, machine learning algorithm that aims to help classify HBV patients. By improving clinical decision-making, patient outcomes are enhanced. Early detection and treatment can have a significant impact on improving patients' quality of life and in reducing the overall prevalence of HBV in Nigeria.

A life-threatening liver infection caused by Hepatitis B virus (HBV) affects over 296 million people globally. Australian researchers developed a machine learning algorithm that detects HBV using simple blood tests, bringing early detection within reach. It offers high accuracy with less cost than enzyme immunoassays. The tool is set to undergo validation using data from different sources to ensure robust and applicable results. Learn how this medical breakthrough can save lives. (character count: 152)

Ezra's AI-powered cancer screener uses affordable MRI imaging tech to detect early signs of cancer in up to 13 organs. A recent FDA clearance permits Ezra Flash, the company's newer AI tech, to rapidly produce high-quality imaging for a more affordable price. The company-aimed to offer an end-to-end platform that's accessible to all-and CEO Emi Gal aims to create a $500 full-body MRI scan that everyone can afford. Even more, the AI-tech-based screening has helped one of its patient's spot a life-threatening brain tumor before its condition worsened. Ezra operates currently in five US states, with ambitions to expand nationwide.

This article explores the alarming increase in the number of diabetes cases in India and the possible solutions to reduce its burden on the country. Dr Arvind Desai, a well-known diabetologist, shares his insights and recommendations on how lifestyle changes, early detection and proper treatment can curb the growth of diabetes cases. Read this article to find out more!

This new study findings may become a “game changer” in the efforts to identify people with Parkinson's disease. UTHealth's McGovern Medical School researchers, headed by Claudio Soto, PhD and funded by The Michael J. Fox Foundation, developed a patented technology employing misfolded alpha-synuclein to detect the disease accurately. The technology has been used to survey 1,123 participants from around the world, giving a diagnosis accuracy of up to 98.6%. This breakthrough offers a greater chance of earlier detection and better therapeutic treatments.