Three years into the future, doctors will be empowered with a wide array of cloud technologies and will become the most efficient they have ever been. Physicians and artificial intelligence systems will have the ability to know your health status, perhaps even before you do, thanks to the combination of three important factors: artificial intelligence, cloud electronic medical records/digital medicine and sensor technology.
IBM’s Watson For the past year has been building up medical skills, scanning through exam books to learn the basic principles of diagnosis and learning to parse the often-confusing mess of data in electronic health records. Obviously IBM’s goal is to create a digital assistant that can point doctors to crucial data and likely diagnoses based on a patient’s medical history at this stage. If IBM can get the system working, it could be a lifeline to overworked doctors and overcrowded hospitals. The Association of American Medical Colleges estimates the US will be short as many as 45,000 primary care doctors by 2020. Here’s how IBM Watson builds its concept map.
As I have mentioned above that Artificial Intelligence algorithms would play a key role in building a virtual assistant for human doctors and then evolve into a full time iDoctor over a period of time. Using natural language processing and artificial intelligence, AI should guide patients through a number of healthcare processes. It can answer questions about insurance, find doctors, track personal goals, support adherence to treatment regimens, suggest healthy food choices, send reminders, share lab results, and communicate basic pieces of information — all through a mobile device. The role of cloud powered digital medicine and electronic medical records is the second most important component of this iDoctor system. Electronic medical records have helped healthcare providers become more efficient by offering better patient care. Yet, this type of document organization, order placement, laboratory check-ups, digital imaging, and e-prescribing are only the surface of the true potential laying within EMRs. Analyzing medical records and mapping the information can also yield key performance indicators summaries, helping doctors to identify who did well and why, and who did not.
The third most important component would be wearable sensors. Each one of us would be capturing our own personal health data. Currently, sensors can give us blood pressure, number of respirations, calories burned, heart rate during rest and exercise, oxygen saturation, etc.In addition what this means is that with the proper developed platform, incorporating all these data could alert patients, or signal alarms that would recommend them to visit their healthcare provider before the condition starts worsening. This brings pre-emptive and preventative medicine to a different level. It would be more exciting when we consider updating this information into the digital medical records and having them analyzed by Cloud Analyst called iDoctor.
These changes will modify how medicine is practiced globally. It is a medical revolution that will lead to the improvement in the quality of life of millions of people. Robots are already capable of doing high precision surgeries and it is about time that diagnostic medicine also becomes more data oriented instead of being totally whimsical. I know what doctors would say that no machine can have human insight. Perhaps 1% or less truly genius diagnostic physicians or fictional characters like House M.D. would always be better than machines. But iDoctor would always be more potent than 99% doctors. That is what the future holds for all of us. 1% or less plutocratic human NEOs (Fictional character in Matrix Movie) of our world would be thinkers, machines would be the laborers and 99% population will survive on government welfare safety nets till they evolve into new idea thinkers.The world has always been ruled by 1% or less. We should let a human doctor compete with a Cloud powered iDoctor and compare the accuracy of both Diagnosis. IBM’s Watson is already helping human doctors with diagnosing Cancer. Here is an overall architecture of how such a system might work.
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