News: Medical AI in Healthcare

Tasks that are not directly related to the treatment of patients

Using data from a standard CT scan, the non-invasive HeartFlow Analysis creates a personalized 3D model of the coronary arteries and analyzes the impact that blockages have on blood flow.
  • HeartFlow creates a personalized, digital 3D model of the arteries.
  • Powerful computer algorithms solve millions of complex equations to assess the impact that blockages have on blood flow.
  • The result is a color-coded map that aids clinicians in determining, vessel-by-vessel, if sufficient blood is reaching the heart.

Improving the emergency departments

Artificial intelligence systems and machine learning can cope with more than just diagnosis. For example, at the end of May, the University College London Hospital in Bloomsbury (UCLH) announced that it would use AI systems to identify patients who really need emergency medical care.

In March, only 84.5 per cent of its patients arriving in A&E were seen within the target four hours. This eight-year low is the worst since records began in 2010. Source: Dailymail

Searching for new knowledge

Treatment practices followed by doctors tend to become obsolete. New methodologies, new research and drugs are emerging. Back in 2004, researchers studied the content of 341 medical journals and found that the total number of monthly publications exceeded 7000.

Creating new drugs

The experience of pharmaceutical companies shows that it takes about 12 years from pre-clinical trials to drug approval. At the same time, only 0.1% of the “candidate drugs” get to clinical tests. Approval is received by only 20% of them.

AtomNet predicting candidate treatments for Ebola infection — this prediction resulted in the lead molecule now awaiting animal trials.

More where this came from

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Blockchain infrastructure aimed to host, train and use artificial intelligence (AI) in healthcare. Our website: https://skychain.global/