utilizes machine learning and computer vision to identify morphology and rapidly characterize cell types from a tiny finger prick of blood. Athelas CEO Tanay Tandon explains, “clinicians and health plans are able to save thousands of dollars annually per-patient by reducing hospitalizations, detecting adverse events earlier from frequent Athelas tests, and by keeping patients safely compliant on necessary therapeutics.
The interaction of speed, cost and accuracy can do amazing things for patients. However, the promise of improved speed, cost, or accuracy alone is often insufficient to meaningfully impact patient care. Anthony Bertrand, MD, MBA explains,"there are many companies trying to sell software that improves the diagnostic accuracy of a single test by x%, especially in fields involving visual diagnosis or imaging like pathology or radiology, only to be received by skepticism or dismissal.
Fortunately, increasing cost pressures and rewards, the publication of health outcomes data, the emergence of payment methods like bundled payments and the availability of EMR data for analysis could help accelerate the benefits of AI in healthcare. The key is aligning great technology with the realities of the healthcare industry. As Viz.ai CEO Chris Mansi, MD, MBA puts it, “just as many companies understand now that an algorithm is not a product, at Viz.
The author’s examples are mediocre (at best). The prime example of utilizing AI in healthcare and biotech is the collaboration between MSFT and ADPT.
MentalHealthMatters
politicians are the top left
FREE THE USA!! 🇺🇸
IBMWatsonMedia
no thank u, Scandinavia has done enough
brayanruiiz_