Why Facebook wants to help with medical imaging

Here’s what I think:

Solving big-world problems helps retain talent. Facebook, like the additional large technology players, can afford to staff its engineering team with machine learning experts which few additional companies can afford. yet those people will probably want to do more than help optimize engagement to maximize advertising revenue — they’ll want to work on hard problems which could help a lot of people as well as potentially even save lives. This specific project might fit the bill. So talent retention can be probably part of the reason.

which’s a huge market with untapped opportunities for companies which understand data. The health sector can be worth about $3 trillion, as well as the traditional tech companies still don’t have much presence there, despite years of effort. There are huge business opportunities in developing algorithms which can determine physician quality, patient outcomes, speed up routine tests, make predictions about those which are likely to get sick, as well as so on. This specific information was previously trapped in hospital servers. currently which’s starting to be used for research, as well as ultimately could be used commercial products.

We know which Facebook within the past few years has hired a few health experts to approach hospitals to work on medical applications, which involve sharing de-identified data. yet I believe we’ll see every tech company via Alphabet to Amazon, as well as the smaller start-ups, find ways to access these datasets.

Facebook carries a lot of experience with images. Thanks to its longstanding focus on photo sharing, Facebook has the right mix of experts on its staff to work with imaging data.

Think about its expertise in photos, where which can almost immediately figure out who should be tagged among countless potential options.

Imaging data can be a particularly attractive subset of medical data, too. Radiologists are used to incorporating computers into their work, as well as they are overloaded with piles of imaging data which they don’t have time to analyze. NYU alone does two million imaging exams per year, according to Daniel Sodickson, NYU’s vice chair for research in radiology. Hospitals across the planet could benefit via tools which could speed up as well as bring brand new efficiency to This specific process, as well as might be willing to pay for which.

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