The use of Artificial Intelligence (AI) in healthcare has the promise to reach a new era with companies like Imagia leading the way. Founded in 2015, the AI healthcare company’s purpose is to improve outcomes for patients, with a specific focus on oncology. Imagia does this by leveraging information from routine medical imaging, reports and other data.
Healthcare AI requires data, doctors, distribution
Although there is no doubt of its potential, we have yet to see the proper utilization of AI in health care. There are many challenges to developing and implementing this technology into routine care, including access to good quality data, staying clinically relevant, and getting solutions directly to patients and physicians.
In Canada alone, tens of millions of X-ray and mammography scans are performed each year, producing quality imaging data that is only used a handful of times. This patient data goes unused after their first or second doctor’s visit, when it could instead continue to provide valuable information, alongside tissue, blood and molecular tests through AI.
While access to quality data will help detect and solve clinically relevant problems, solutions need to reach patients to make a real difference. One major roadblock remains the limited scale of collaboration between expert communities of clinicians, AI researchers, and health care industry players.
By fostering a collaboration environment between clinicians and AI researchers, AI solutions — driven by clinician insight — can be developed to enable personalized care. Instead of trying to fit existing AI research into a clinical environment, health care practitioners can be involved from the beginning to determine the best fit for data-driven results.
Personalized healthcare for personal journeys
Imagia’s solution is its Evidens ecosystem, which brings together creative minds in AI and healthcare to drive the discovery and adoption of clinically relevant biomarkers and ensure solutions get to patients.
Cancer is a disease that touches many Canadians, and early diagnosis is one way to impact patient survival. AI-driven solutions will be used by medical-device manufacturers that provide clinical decision support for doctors, helping with early detection, more accurately diagnose tumours, and personalize treatment options — the opportunities for improving patient outcomes are endless. No two cancers are the same, and neither are two patient journeys. Each journey is personal, and needs to be supported by personalized AI healthcare.
