Stronger, more accurate diagnostics to save and change lives

AI and deep learning are supporting medics in providing quicker and more accurate diagnosis

Today, practitioners, clinics, hospitals and health-service budgets are all under increasing pressure. AI and deep learning can support improved and more effective diagnosis, and support healthcare organizations in a myriad of other ways as well. Deep learning could open the door to a new future for diagnostics.

A healthcare game-changer for medical professionals and patients

AI can act as a “second opinion” for physicians, particularly lending decision support to newer practitioners. Among practitioners of all levels, diagnosis aided by machine learning would lend patients much-needed diagnostic backup.

Matching a patient’s symptoms to a disease is a skill at the heart of successful healthcare. Historically, diagnosis has relied upon the subjective expertise and judgment of practitioners in each individual patient case. AI can profoundly increase the success rates of diagnostics by offering insights from patterns within symptoms from a large number of patients. Instead of a doctor being limited to what they can currently see, with machine learning and deep learning, they have insight into cases around the whole world — not just local and personal experience — to assist with diagnosis.

The World Health Organization estimates a 14 million shortfall of health workers by 2030

AI also offers more accurate and timely ability to pinpoint where cancer cells lie. Using current cancer-treatment methods like radiotherapy, it’s challenging to pinpoint exactly which cells are cancerous and which are healthy with enough accuracy to avoid killing healthy cells. Instead, in the cancer domain, physicians often overcompensate and kill more cells than is actually necessary, compromising patient health. In addition, between cancer diagnosis and treatment, a tumor often moves, which means the wrong place receives irradiation. And that delay can be quite long, due to a shortage of experts.

This scenario has always been the best possible solution, but now, deep learning has a much more precise answer. AI can aid in more precise diagnosis within areas like tumor segmentation, allowing practitioners to work with real-time indications rather than waiting for responses, and making it much easier for caregivers to plan and prioritize. Patients could benefit from a shorter wait time to get answers to their pressing health questions.

Get more insight into how Peltarion supports healthcare and diagnostics

The Peltarion Platform is set up to support deep learning methods and replicate groundbreaking research results while enabling non-experts to both apply and better understand the deep learning process. The Peltarion Platform has already been used to segment skin lesions and locate brain tumors, making segmentation more precise and acting as decision support for doctors. Try the Tutorial Skin lesion segmentation to learn how to build a model that will solve an image segmentation problem in the healthcare domain.

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