Creepy software developed by Amazon reads patients’ medical records

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A creepy medical tool developed by Amazon uses artificial intelligence to spot whether you are ill long before your doctor.

The project, called Amazon Comprehend Medical, scans through your medical record for key data points and then tells its medical professional customers what look out for.

This means it can detect patterns in the data much faster than a doctor, suggesting diagnoses for underlying conditions.

The use of health records by companies – now a market worth $3.2 trillion (£2.5tn) – has been heavily criticised over privacy concerns.

However, developers say the data processed by the firm’s algorithms is encrypted and will only be seen by customers and not shared with Amazon Web Services. 

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Amazon is working on creepy new software that reads patient medical records and then tells doctors what illnesses to look out for (stock image)

Amazon is working on creepy new software that reads patient medical records and then tells doctors what illnesses to look out for (stock image)

According to the firm, Amazon Comprehend Medical means doctors could access medical information on specific conditions, dosage, strength and frequency.

The language processing AI scans information like doctor’s notes, clinical trial reports and patient health records. 

In order to use the service, which is currently not available commercially, users will have to upload their health records to Amazon’s cloud service.

The software then runs through this information and analyses the data, which according to the firm is only shared with the customer.

‘Additionally, the service identifies the relationship among the extracted medication and test, treatment and procedure information’, the developers said.

‘For example, the service identifies a particular dosage, strength, or frequency related to a specific medication from unstructured clinical notes.’

Now more than 80 per cent of US hospitals have electronic health records, compared to just 10 per cent in 2008, according to Wall Street Journal.

‘The majority of health and patient data is stored today as unstructured medical text, such as medical notes, prescriptions, audio interview transcripts, and pathology and radiology reports’, Dr Matt Wood, general manager of artificial intelligence at Amazon Web Services, wrote on a blog post.

Amazon Comprehend Medical claims to help medical experts identify these reports ‘with high accuracy’, he said.

During tests, the software was reported to work better than other published efforts. 

An Amazon spokesperson clarified that results of the data analysis `are not shared with the patient, it is provided to the customer.’

The spokesperson added: `Amazon is not accessing or using healthcare records. Again, customers maintain complete control of their data, which is all encrypted and secured. AWS [Amazon Web Services, a business unit within Amazon.com] does not have access to this information. AWS also does not store any data processed by Comprehend Medical and once analysis is complete, the output is delivered solely back to the customer.’

`Customers don’t necessarily have to upload health records, they can select sections of information they want to analyse/understand.’

`Comprehend Medical is HIPAA eligible and is covered by the AWS Business Associate Agreement (BAA), which is an AWS contract that is required under HIPAA rules to ensure that AWS appropriately safeguards protected health information (PHI). The BAA also serves to clarify and limit, as appropriate, the permissible uses and disclosures of Protected Health Information (PHI) by AWS, based on the relationship between AWS and our customers, and the activities or services being performed by AWS.’

Amazon is one of many firms increasingly showing an interest in the lucrative market of health care. 

Earlier this month french concerns about patient data were raised after Google announced plans to bring the health division of its DeepMind artificial intelligence company more closely under its control.

The move means Google will manage the subsidiary’s Streams app, which processes NHS patient data to alert doctors if someone is at risk of developing kidney disease, potentially saving half a million hours of paperwork and helping to detect illness quicker.

UK-based DeepMind came under scrutiny last year after UK data watchdog the Information Commissioner’s Office ruled that the Royal Free NHS Foundation Trust illegally provided the data of around 1.6 million patients as part of a trial.

‘The staff of DeepMind Health promised they wouldn’t give data to Google, so the owners of DeepMind handed the Health team to Google, data included,’ said Phil Booth, co-ordinator of medConfidential, a campaign group for confidentiality and consent in health and social care.

The project, which is called Amazon Comprehend Medical, uses language processing AI to pick out key data points from digitised medical notes (file photo) 

The project, which is called Amazon Comprehend Medical, uses language processing AI to pick out key data points from digitised medical notes (file photo) 

‘DeepMind repeatedly, unconditionally, promised to never connect people’s intimate, identifiable health data to Google,’ tweeted New York University Law and Tech researcher Julia Powles. ‘Now it’s announced… exactly that. This isn’t transparency, it’s trust demolition.’

A few months ago it was revealed a secretive unit of Amazon is believed to be focusing on a variety of health issues, including cancer research and medical records, as well as other areas like logistics,CNBC reported, citing sources close to the situation. 

The team is being referred to internally as ‘Grand Challenge’, but also operates under the monikers ‘1492’ and ‘Amazon X’.  

It’s being spearheaded by the creator of Google Glass, Babak Parviz, as well as slew of Google X engineers and executives from health startups, according to CNBC.

The group has grown swiftly, adding more than 50 people to its ranks since 2014. 

Little is known about what Grand Challenge is working on, though a few details have trickled out. 

It’s been charged with working on a variety of ambitious ventures, as evidenced by a an internal job posting, which quotes astronomer Carl Sagan, saying: ‘Somewhere, something incredible is waiting to be known’. 

At a recent health care conference, Parviz alluded to a project that’s been in the works ‘for some period of time and…relates to what happens to older people’. 

The team is working with the Fred Hutchinson Center in Seattle to devise ways that machine learning can be used to help prevent and cure cancer.

HOW DOES ARTIFICIAL INTELLIGENCE LEARN?

AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn.

ANNs can be trained to recognise patterns in information – including speech, text data, or visual images – and are the basis for a large number of the developments in AI over recent years.

Conventional AI uses input to ‘teach’ an algorithm about a particular subject by feeding it massive amounts of information.   

AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn. ANNs can be trained to recognise patterns in information - including speech, text data, or visual images

AI systems rely on artificial neural networks (ANNs), which try to simulate the way the brain works in order to learn. ANNs can be trained to recognise patterns in information – including speech, text data, or visual images

Practical applications include Google’s language translation services, Facebook’s facial recognition software and Snapchat’s image altering live filters.

The process of inputting this data can be extremely time consuming, and is limited to one type of knowledge. 

A new breed of ANNs called Adversarial Neural Networks pits the wits of two AI bots against each other, which allows them to learn from each other. 

This approach is designed to speed up the process of learning, as well as refining the output created by AI systems. 



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