IBM’s Watson did not just do that?

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Wearable industry growth figures are at top of the charts. Every fortnight wearable start-ups are either closing funding rounds , or been acquired and in some cases hosting IPO.

All this limelight and fame for one reason, that being , these devices can record data. Analysis of data and subsequent predictions to users still remains work in progress.

IBM’s Watson however, is set on a mission to accomplish this work in progress.

Yes, company recently announced collaboration with mobile phone behemoth Apple , where the former would integrate its smart computer to latter’s wearable ( watch). This all magic takes place in app called Cafewell Concierge, which is powered by Watson’s adaptable and self learning code.

Partnership of this type came to limelight only recently and has been IBM Watson’s first of its kind deal with Apple.

This Welltok developed app uses Watson’s cognitive trait to turn Cafewell Concierge more understanding companion by days , primarily because Watson learns, adapts and performs.

Combo can become one stop solution for health , exercise, nutrition and other aspect of human life management.

Unlike any other wearable which puts the recorded data usage and analysis to question, situation in this case seems pretty convincing. Primarily because data recorded is going in training predictive response programing of Watson.

While some of the existing wearable providers,quote to deliver the similar offerings, we all are aware about how deceiving can the cloud and app analysis be(Not to forget the blurred line that exist on when a app is FDA regulated and when its not). Watson super computer on other hand has proved instrumental time and again proving its credibility in this new venture.

Time alone would say if this IBM- Apple journey sees happy and productive ending, as of now the platform is warming up to IBM employees alone. The employees who had privilege to buy Apple smart watch at subsidized rates.

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Can computers replace surgeons?

Watson

4 out of 10 developments in healthcare revolve around automating systems, with fundamentals flagged to robotics. Every aspect from diagnosing to surgeries has seen a great amount of inclination towards robotics. All these are routed to one greater reason, which is improvising healthcare and making its technologies more precise, quick and economical.

Human errors can be reduced significantly by protocol adherence however there (Human = Surgeons and Physicians) availability on the account of increased patient head counts remain daunting issue for HCP (Health Care Personnel).

Making an effort to address this challenge is IBM which has begun training Watson computer to read CT & other images. While surgery and diagnosing areas of healthcare witnessed development from the likes of Intuitive Surgical and Scanadu, image interpretation was first of its kind development in healthcare.

The development quest begun just after IBM had acquired company Merge, a healthcare player having a right material (30 Billion Medical Images) for streamlining venture’s vision for healthcare. Merge Health houses close to 30 billion medical images which can act as potential feedstock for designing this image reading computer. According to claims the device could read CT images, MRI scans , ECGs and other image types for patient health interpretation.

According to industry news features the fundamentals of this development will include making computer scan through various image samples from subjects (patients and healthy people) and help structure an algorithm that differentiates the image with abnormalities .Though various surgeons from around the globe had a mixed opinion on this quest, majority of them are inclined in saying that this innovation is very unlikely to replace doctors and is just going to help them become better surgeons. The statement was made on the grounds of technology tip that happened years back, a trend carrying similar air and claims around it. Development in reference is transition from film to digital, an activity that contributed to their roles betterment in healthcare ecosystem.

Image reading computer development’s thought and materialization started because of the increasing need of patients for a better and quicker screening solution. While the hospital houses only certain head count of care takers, world was in dire need of a system that can predict nature of issue by looking at scan results (Images and Graphs). If the problem was trivial and does not need surgeon’s intervention, it saves cost; else it helps take the issue reach surgeons attention quickly.

Debate on, if it is going to replace surgeons or not is secondary , what is important here is non-core companies are developing healthcare through their expertise skill sets and are not hesitant to shell out cash either for technology licensing , partnership or in this case an acquisition. While the healthcare’s future always seems to be blurred on account of growing ailments, developments like this provide little clarity to the image, and for sure come out as an assuring one.

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