Optellum enables lung disease patients to be treated at the earliest stage and cured.
They have developed the world’s first AI-based Decision Support software to enable physicians to manage lung nodule patients optimally.
Their platform helps clinicians identify and track at-risk patients and speed up decisions for those with cancer while reducing unnecessary procedures.
They are developing an Artificial Intelligence software platform to support clinicians in lung cancer nodule management.
Optellum and partners have gathered the largest real-world dataset and from this, using Artificial Intelligence and Machine Learning, have developed a solution to enable clinicians to identify at-risk patients and to guide lung cancer management.
Optellum was founded so that every lung cancer patient is treated at the earliest possible stage, and cured. They are redefining early interception of lung disease, by enabling every clinician, in every hospital, to manage their patients in an optimal way.
Their first product is the first Clinical Decision Support software for personalised early diagnosis & treatment of lung cancer, based on Artificial Intelligence & Machine Learning applied to the world’s largest clinical dataset.
They’re a team of world-leading medical imaging software, AI, and clinical experts who met at Oxford’s world-renowned computer vision laboratory. Between them, they have track records of bringing innovation to market through over 10 start-up companies, resulting already in 5 trade-sales and one IPO.
Optellum is backed by an Advisory Board comprising world-leading clinicians (global authors of medical guidelines) and experts in deep learning.
They’re building up their development team – join our fight against cancer, working together with former software engineers from top technology companies (Amazon, Facebook, Redhat) and veterans of medical imaging startups.
Optellum and NCIMI
Optellum has partnered with NCIMI (National Consortium of Intelligent Medical Imaging) to investigate the role that AI can play in medical imaging.
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