Long time UK-based health-focused social network HealthUnlocked has flipped the switch to make its mobile appglobally available, aiming to boost access to its network and feed more data into machine learning matching algorithms it began applying to the platform earlier this year idea being to help people with the same health circumstance find each other so that they are able to share information and support.
The new app builds the HealthUnlocked network most accessible than ever before and we expect more people to use the platform as a result, entailing more data is collected and users receive highly tailored recommendations, is its concise take on broadening the apps reach.
While it launched the app back in February, HealthUnlockeds website put in place in 2012 and currently has more than 700,000 registered users and around 40 million visitors annually to~ 700 online support groups. The majority of group offer support for people with long term conditions, but the platform also offers general wellness communities, with groups focused on topics such as healthy eating and fitness.
Users can join multiple online communities, posting to share and interact publicly with other members. They can also individually message others, tells if they want to privately discuss a shared health condition.
Theres no requirement to use real identities within the app indeed, consumers are fostered not to do so, given the sensitive nature of discussions. While support groups are moderated by relevant not-for-profit organizations which can also feed information in local communities. HealthUnlocked tells it has more than 700 charity and non-profit spouses at this point.
The app has been developed around the platform and its big user base, it mentions. Every time a customer writes something within the platform, we now operate 638 algorithms, allowing us to understand the subject and health context of what has been written. For instance, if you write about weight loss understanding the the context it was written in for example anorexia, rather than a new cancer drug or the start or a consumers operating government makes a huge difference when you are building surmises about what the user is interested in.
The information it needs to request at onboarding is less than ever before on account of leaning on machine learning algorithm to extract custom insights from consumers interactions.
Initial onboarding collects gender, health concerns and diagnosed circumstances to initially recommend online communities. We then use our technology and algorithms to create a health profile by understanding their behaviour, the pages they read, or conditions they write about. They are then recommended further communities to join and other useful connects. This is a constantly evolving process based on the individuals activity, it adds.
The UK company has raised 5M to date from private investors from the tech and health sectors in the UK and Silicon Valley, including Nick McKeown( Nicira, Barefoot) and Professor Walter Nimmo CBE( Inveresk ).
It monetizes via matching consumers to relevant content, products and services, based on what it reads about them as they use the network. It mentions a big part of its commercial activity involves matching people to clinical trials and market research opportunities.
While another strand of its business is licensing a care planning tool it built for cancer patients, which is run in partnership with Macmillan Cancer Support. This is being used in more than 100 hospitals across the UK at this level, and is due to be rolled out to all hospitals in England later this year.
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