AI News, The Patient Will See You Now artificial intelligence

Can this technology put an end to bullying?

Breaking up with your first love is hard to do, but at the age of 18, it was a particularly traumatic experience for Nikki Mattocks.

Even in our modern, progressive society, it is too often overlooked and commonly dismissed as a rite of passage, but bullying affects between a fifth and a third of children at school.

Yet research has shown that bullying can leave a lasting scar on people’s lives, causing long-term damage to their future health, wealth and relationships.

His team trained a machine learning algorithm to spot words and phrases associated with bullying on social media site AskFM, which allows users to ask and answer questions.

Researchers at McGill University in Montreal, Canada, are training algorithms to detect hate speech by teaching them how specific communities on Reddit target women, black people and those who are overweight by using specific words.

One survey in 2017 found that 42% of teenage users have experienced bullying on Instagram, the highest rate of all social media sites assessed in the study.

“I now know firsthand what it’s like to feel you’re in a safe place, being relaxed and open and unguarded, and then, on a word, to be suddenly be ripped into.”

Recent revelations of sexual harassment within major technology firms in Silicon Valley have shone a light on how bullying and discrimination can impact people in the workplace.

time-stamped record of an incident around when it occurred could make it harder to cast doubt upon evidence later drawn from memory, as critics of Christine Blasey Ford attempted to do after she gave testimony against Brett Kavanaugh.

Trained on more than 300,000 US and Canadian court case documents, it uses natural language processing to assess whether a user has been a victim of sexual harassment in the eyes of the law, and generates an incident report, which a user can hand over to human resources or the police.

The algorithms were able to predict whether a patient would attempt to end their life in the week following an instance of self-harm “AI can gather a lot of information and put it together quickly, which could be helpful in looking at multiple risk factors,”

The algorithms were able to predict whether a patient would attempt to end their life in the week following an instance of self-harm, with an accuracy of 92%.

“We can develop algorithms that rely only on data already collected routinely at point of care to predict risk of suicidal thoughts and behaviours,”

“Although accurate knowledge of who is at risk of eventual suicide attempt is still critically important to inform clinical decisions about risk, it is not sufficient to determine imminent risk.”

They asked 34 participants to think of 30 specific concepts relating to positive or negative aspects of life and death while they scanned their brains using an fMRI machine.

The computer was able to discriminate with 94% accuracy between nine people experiencing suicidal thoughts who had made a suicide attempt and eight who had not, by looking at these differences.

He believes that one day therapists could use this information to design a personalised treatment for someone having suicidal thoughts, perhaps working with them to feel less shame associated with death.

For example, when someone types a query into Google related to attempting suicide, the search engine offers them the help line of a charity such as The Samaritans instead of what they were looking for.

In serious cases, Facebook may contact local authorities and has worked with first responders to carry out more than 1,000 wellness checks so far Facebook trained their algorithms to identify patterns of words in both the main post and the comments that follow to help confirm cases of suicidal expression.

All this data is funnelled into another algorithm that is able to work out whether a Facebook user’s post should be reviewed by Facebook’s Community Operations team, which can raise the alarm if it thinks someone is at risk.

Maria Liakata, an associate professor at the UK’s University of Warwick, is working on detecting mood changes from social media posts, text messages and mobile phone data.

While this approach could raise privacy concerns, thousands of people are already willingly sharing their deepest thoughts with AI apps in a bid to tackle depression, which is one predictor of suicide.

VIDEO: Development of Artificial Intelligence to Aid Radiology

Organizations who are embarking on an enterprise imaging journey share many of the same questions and concerns regarding how to best optimize workflow across providers, departments and facilities;

In this video we address the key challenges and considerations faced by organizations undertaking an Enterprise Imaging journey, and how a trusted partner can contribute valuable expertise and guidance that enable healthcare organizations and vendors of any size to successfully tackle even their most challenging enterprise imaging initiatives.

VIDEO: How to Prepare a Patient for a Cardiac CT Scan

Organizations who are embarking on an enterprise imaging journey share many of the same questions and concerns regarding how to best optimize workflow across providers, departments and facilities;

In this video we address the key challenges and considerations faced by organizations undertaking an Enterprise Imaging journey, and how a trusted partner can contribute valuable expertise and guidance that enable healthcare organizations and vendors of any size to successfully tackle even their most challenging enterprise imaging initiatives.

The Patient Will See You Now

Although not yet released on the market,  his team at Scanadu created the Scanadu Scout which you can hold to your temple and it will give you your health results—everything from blood pressure, temperature, heart rate, and pulse oximetry—in just 10 seconds. I caught up with Walter to discuss his sci-fi esque predictions on the future of health.

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