{"id":53836,"date":"2024-12-12T09:53:55","date_gmt":"2024-12-12T09:53:55","guid":{"rendered":"https:\/\/www.innovationnewsnetwork.com\/?p=53836"},"modified":"2024-12-12T09:53:55","modified_gmt":"2024-12-12T09:53:55","slug":"ai-blood-test-revolutionises-early-breast-cancer-detection","status":"publish","type":"post","link":"https:\/\/www.innovationnewsnetwork.com\/ai-blood-test-revolutionises-early-breast-cancer-detection\/53836\/","title":{"rendered":"AI blood test revolutionises early breast cancer detection"},"content":{"rendered":"

A groundbreaking new screening method combining laser analysis with artificial intelligence (AI) could redefine early cancer detection<\/a>.<\/h2>\n

Developed by researchers at the University of Edinburgh, this innovative approach identifies patients with breast cancer at the earliest stage, known as stage 1a<\/a>. According to a recent study, the AI blood test offers a non-invasive, rapid, and highly accurate alternative to existing diagnostic tools.<\/p>\n

The study’s collaborators included researchers from the University of Aberdeen, the Rhine-Waal University of Applied Sciences, and the Graduate School for Applied Research in North Rhine-Westphalia.<\/p>\n

Early detection: The game-changer for cancer survival<\/h3>\n

Current breast cancer screening methods, including physical exams, X-rays, ultrasounds, and biopsies, often identify the disease in later stages or rely on age-based and risk-group screenings. Early detection, however, is crucial for successful treatment and long-term survival.<\/p>\n

The new AI blood test marks a significant leap forward, detecting stage 1a breast cancer by analysing subtle changes in the bloodstream\u2014changes that conventional tests cannot pick up.<\/p>\n

These minute chemical alterations in blood plasma signal the early onset of cancer and hold the key to timely intervention.<\/p>\n

Dr Andy Downes, of the University of Edinburgh’s School of Engineering said: “Most deaths from cancer occur following a late-stage diagnosis after symptoms become apparent, so a future screening test for multiple cancer types could find these at a stage where they can be far more easily treated.<\/p>\n

“Early diagnosis is key to long-term survival, and we finally have the technology required.”<\/p>\n

The science behind the AI blood test<\/h3>\n

The innovative process combines Raman spectroscopy \u2013 a laser-based analysis technique \u2013 with machine learning, a powerful AI tool. Here’s how the AI blood test works:<\/p>\n

    \n
  1. Laser analysis<\/strong>: A laser beam is directed at blood plasma samples. The light interacts with the plasma and its properties are measured using a spectrometer.<\/li>\n
  2. Chemical signature detection<\/strong>: The spectrometer reveals subtle chemical changes in cells and tissues, which serve as early indicators of disease.<\/li>\n
  3. AI interpretation<\/strong>: Machine learning algorithms analyse these chemical signatures, identifying patterns and classifying the samples with remarkable precision.<\/li>\n<\/ol>\n

    In a pilot study involving 24 participants \u2013 12 with breast cancer and 12 healthy controls \u2013 the method achieved a 98% accuracy rate in detecting stage 1a breast cancer.<\/p>\n

    Additionally, the test distinguished between the four main subtypes of breast cancer with more than 90% accuracy, paving the way for tailored treatment options.<\/p>\n

    The blood samples were provided by the Northern Ireland Biobank and the Breast Cancer Now Tissue Bank.<\/p>\n

    A multicancer future<\/h3>\n

    While this revolutionary AI blood test currently focuses on breast cancer, the research team aims to expand its application to other cancer types.<\/p>\n

    Early-stage detection across multiple cancers could dramatically improve survival rates and treatment effectiveness.<\/p>\n

    Dr Downes and his colleagues envision building a comprehensive database to support a future multicancer screening tool.<\/p>\n

    A pathway to personalised medicine<\/h3>\n

    One of the most exciting aspects of this AI blood test is its ability to classify cancer subtypes. By distinguishing between the four main types of breast cancer, the test could enable more personalised and effective treatment strategies.<\/p>\n

    Personalised medicine, which tailors treatments to individual patients based on their specific cancer characteristics, is increasingly recognised as the future of oncology.<\/p>\n

    The ability to identify cancer subtypes early on ensures that patients receive therapies best suited to their unique needs, improving outcomes and reducing unnecessary side effects.<\/p>\n

    The research team is eager to scale up their study, involving larger and more diverse participant groups.<\/p>\n

    By refining their techniques and expanding their database, they hope to bring this promising technology closer to clinical implementation.<\/p>\n

    As this AI blood test continues to evolve, it holds the potential to revolutionise cancer screening and treatment, saving countless lives in the process.<\/p>\n

    By unlocking the power of AI and laser technology, researchers are ushering in a new era of cancer diagnostics.<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

    Discover how an AI blood test detects early-stage breast cancer with 98% accuracy, paving the way for personalised cancer screening.<\/p>\n","protected":false},"author":15,"featured_media":53839,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[10551],"tags":[24493,849,24183],"acf":[],"yoast_head":"\nAI blood test revolutionises early breast cancer detection<\/title>\n<meta name=\"description\" content=\"Discover how an AI blood test detects early-stage breast cancer with 98% accuracy, paving the way for personalised cancer screening.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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