Black-Box Algorithms: Ready For Medical Use? : Shots

Black-Box Algorithms: Ready For Medical Use? : Shots – Health News It’s hard for humans to check algorithms that computers devise on their own.

Zech and his medical school colleagues discovered that the Stanford algorithm to diagnose disease from X-rays sometimes “Cheated.” Instead of just scoring the image for medically important details, it considered other elements of the scan, including information from around the edge of the image that showed the type of machine that took the X-ray.

Black-box algorithms are the favored approach to this new combination of medicine and computers, but “It’s not clear you really need a black box for any of it,” says Cynthia Rudin, a computer scientist at Duke University.

She is pushing back against a trend in the field, which is to add an “Explanation model” algorithm that runs alongside the black-box algorithm to provide clues about what the black box is doing.

Shah developed an algorithm that could scan medical records for people who had just been admitted to the hospital, to identify those most likely to die soon.

It is equally important to avoid misuse of an algorithm, for example if a health insurer tried to use Shah’s death-forecasting algorithm to make decisions about whether to pay for medical care.

“I firmly believe that we should be thinking about algorithms differently,” Shah says.

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Medical Imaging Classification (TensorFlow Tutorial) – YouTube

This will drastically reduce patient death, save medical practices a lot of money, and aid doctors in the patient care process.

Everyone will win and its important to remember that AI won’t replace doctors, it will become the most powerful tool they’ve ever used.

Published on Apr 22, 2018Can AI be used to detect various diseases from a simple body scan?

From mammograms to cat scans, AI can diagnose a disease better than any human can if given the right training dataset.

Normally, doctors train for years to do this and the error rate is still relatively high.

And once enough AI startups start impacting the field of healthcare, it will become as common a tool as the stethoscope has been.

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Stratasys and Materialise: 3D Printed Medical Models Come to Life

Stratasys PolyJet technology and Materialise FDA-cleared software now most versatile 3D printing system for hospitals and physicians to build anatomical models at the point-of-care.

MINNEAPOLIS & REHOVOT, Israel-(BUSINESS WIRE)-Nov. 26, 2018- Further bringing 3D printed medical models to life, Stratasys is expanding the suite of printers and materials validated by its collaborator Materialise as part of FDA-cleared Materialise Mimics inPrint software.

“The addition of multi-color and multi-material printers to the list of validated printers is aimed to enable healthcare providers to implement a versatile offering that can support their most complex cases across a wide range of surgical specialties on a single printer. At Materialise, we take a hardware-agnostic approach to software development, offering the flexibility to partner with other leaders in the 3D printing industry like Stratasys – a company committed to addressing requirements of the medical community.”

Materialise incorporates 27 years of 3D printing experience into a range of software solutions and 3D printing services, which together form the backbone of the 3D printing industry.

The Stratasys 3D printing ecosystem of solutions and expertise includes: 3D printers, materials, software, expert services, and on-demand parts production.

The statements in this press release relating to Stratasys’ beliefs regarding the benefits consumers will experience from the Stratasys J750, Objet30 Prime 3D Printers or their validation with Materialise, Stratasys’ expectation on the timing of shipping the Stratasys J750, Objet30 Prime 3D Printers or their validation with Materialise, are forward-looking statements reflecting management’s current expectations and beliefs.

These risks and uncertainties include, but are not limited to: the risk that consumers will not perceive the benefits of the Stratasys J750, Objet30 Prime 3D Printers or their validation with Materialise to be the same as Stratasys does; the risk that unforeseen technical difficulties will delay the shipping of the Stratasys J750, Objet30 Prime 3D Printers or their validation with Materialise; and other risk factors set forth under the caption “Risk Factors” in Stratasys’ most recent Annual Report on Form 20-F, filed with the Securities and Exchange Commission February 28, 2018.

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