AI News, Google's AI can spot breast cancer in scans better than human doctors artificial intelligence

Artificial Intelligence Makes Bad Medicine Even Worse

Google researchers made headlines early this month for a study that claimed their artificial intelligence system could outperform human experts at finding breast cancers on mammograms.

In case you haven’t been following the decades-long controversy over cancer screening, it boils down to this: When you subject symptom-free people to mammograms and the like, you’ll end up finding a lot of things that look like cancer but will never threaten anyone’s life.

In practice, most doctors are inclined to treat any cancer that’s discovered as a potential threat, and the question of whether or not mammograms actually save lives is a matter of intense debate.

Some studies suggest they do, others find that they don’t, but even if we take the rosiest interpretations of the literature at face value, the number of lives saved by this massive, widespread intervention is small.

In other words, AI systems like the one from Google promise to combine humans and machines in order to facilitate cancer diagnosis, but they also have the potential to worsen pre-existing problems such as overtesting, overdiagnosis, and overtreatment.

In principle, that power could help us to diagnose any early-stage disease, in the same way the subtle squiggles of a seismograph can give us early warnings of an earthquake.

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(fra:1R3) The journal Nature published a study entitled "International evaluation of an AI system for breast cancer screening"

She was involved with the study and spoke to Wired, "AI programmes will not solve the human staffing crisis - as radiologists and imaging teams do far more than just look at scans - but they will undoubtedly help by acting as a second pair of eyes and a safety net."

It's clear from the number of FDA approved breast specific algorithms, the Google study, and the media response that resulted, that any technology improvement or assistance that can improve diagnostic capability is potentially disruptive, and that breast specific imaging and its improvement is a major priority.

The company has also established Izotropic Imaging Corp, a wholly owned Nevada based subsidiary that will manage operations in the U.S.A. Phone: 1-833-IZOCORP Email: info@izocorp.com Website: izocorp.com This document may contain forward-looking statements that are based on the Company's expectations, estimates and projections regarding its business and the economic environment in which it operates.

Breast Cancer Is Detected Better With AI Machine and More Accurate Than Human Doctors

For women, the dreaded mammary exam is one of the most harrowing medical exams to go through, and with good cause too.

By using machine AI or a computer program that will spot cancerous growth, that might be breast cancer.

This secret weapon of doctors might help them stave off more than 2 million cases of breast cancer each year.

Tools like machine AI helps to narrow the chances of getting a wrong diagnosis of women undergoing mammary exams.

Preventive examination for breast cancer is best done by detecting the most obvious signs of possible breast cancer.

To help deal with inaccurate reading, Google Health experts taught a machine AI to find a positive breast cancer scan of women from the US and UK.

One happy result was a lower number of false positives, that had less positive cancer cases from 5.7% in the US, or 1.2% in the UK.

Detecting of false-negative gives the sufferer a better chance of staving off breast cancer with precise cancer detection too.

Combing the three readers, including the AI will avoid making the wrong reading that might cost the female patients' life.

VIDEO: RSNA President Says Artificial Intelligence is Hottest Tech Advancement in Radiology

Mahadevappa Mahesh, Ph.D., chief of medical physicist and professor of radiology and medical physics, Johns Hopkins University, Baltimore, treasurer of the American Association of Physicists in Medicine (AAPM),a board member of the American College of Radiology (ACR), presented a late-breaking study on how medical imaging radiation dose has started to drop over the past decade.

It shows a decrease of about 20 percent in the radiation dose the U.S. population receives from medical imaging, compared to the NCRP 160 that covered the period of up to 2006.

Mahesh says this shows the impact of using 'as low as reasonably achievable' (ALARA) principals, new dose guidelines outlined jointly by numerous medical societies, and dose reduction initiatives like Image Wisely, Image Gently, and the American College of radiology (ACR) Dose Index Registry.