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AI bests humans in medical diagnosis

Artificial intelligence has proven equal and even better than humans in making some diagnoses.

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  • A review of studies found that AI is at least equal to human healthcare workers in making diagnoses.
  • The conclusion applies to cases where AI looked at images.
  • More real-world tests are necessary to further develop artificial intelligence in medicine.


A review found that artificial intelligence is just as good and even slightly better than human doctors in making medical diagnoses using images.

Researchers carried out a thorough analysis of various studies published since 2012. The AI utilized in the studies used deep learning to classify images based on certain features, which were compared to visuals of diseases.

The study's co-author Professor Alastair Denniston from the University Hospitals Birmingham is both optimistic and cautious about what AI can do. As reported by the Guardian, this sentiment was shared by Dr. Xiaoxuan Liu, the lead author of the study, associated with the same institution.

"There are a lot of headlines about AI outperforming humans, but our message is that it can at best be equivalent," said Liu.


To come to such conclusions, the scientists made an effort to whittle down the list of often-poor studies they looked at from 20,000 to just 14 which had the best quality data. In these studies, the deep learning systems used images from datasets that were separate from the ones used to train them. These same images were then shown to human experts.

The researchers found that AI was able to correctly pinpoint illnesses 87% of the time. That's compared to 86% for healthcare pros. The AI was also right in clearing people of diseases 93% of the time, in contrast to 91% of human experts. One caveat to this statistic was that the healthcare workers tested were not given extra info about patients that they would have had in real-world situations.


Using AI in medicine has a number of potential advantages, from freeing up human doctors to spend more time with patients to customizing treatments and clearing backlogs of necessary diagnoses. AI can also be particularly helpful in environments that lack enough human experts to do this work.The next step in assessing the usefulness of AI in the medical field would be to carry out clinical trials to see if patient outcomes would improve by utilizing deep learning systems.

Check out the new review here.

The biggest problem in AI? Machines have no common sense.

Neom, Saudi Arabia's $500 billion megacity, reaches its next phase

Construction of the $500 billion dollar tech city-state of the future is moving ahead.

Credit: Neom
Technology & Innovation
  • The futuristic megacity Neom is being built in Saudi Arabia.
  • The city will be fully automated, leading in health, education and quality of life.
  • It will feature an artificial moon, cloud seeding, robotic gladiators and flying taxis.
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Why do people believe in conspiracy theories?

Are we genetically inclined for superstition or just fearful of the truth?

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  • From secret societies to faked moon landings, one thing that humanity seems to have an endless supply of is conspiracy theories. In this compilation, physicist Michio Kaku, science communicator Bill Nye, psychologist Sarah Rose Cavanagh, skeptic Michael Shermer, and actor and playwright John Cameron Mitchell consider the nature of truth and why some groups believe the things they do.
  • "I think there's a gene for superstition, a gene for hearsay, a gene for magic, a gene for magical thinking," argues Kaku. The theoretical physicist says that science goes against "natural thinking," and that the superstition gene persists because, one out of ten times, it actually worked and saved us.
  • Other theories shared include the idea of cognitive dissonance, the dangerous power of fear to inhibit critical thinking, and Hollywood's romanticization of conspiracies. Because conspiracy theories are so diverse and multifaceted, combating them has not been an easy task for science.

COVID-19 brain study to explore long-term effects of the virus

A growing body of research suggests COVID-19 can cause serious neurological problems.

Brain images of a patient with acute demyelinating encephalomyelitis.

Coronavirus
  • The new study seeks to track the health of 50,000 people who have tested positive for COVID-19.
  • The study aims to explore whether the disease causes cognitive impairment and other conditions.
  • Recent research suggests that COVID-19 can, directly or indirectly, cause brain dysfunction, strokes, nerve damage and other neurological problems.
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Better reskilling can future-proof jobs in the age of automation. Enter SkillUp's new coalition.

Coronavirus layoffs are a glimpse into our automated future. We need to build better education opportunities now so Americans can find work in the economy of tomorrow.

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