Digital Transformation-How to go about it?

Digital Transformation is the flavor of the season with all talk about bots replacing humans and the Internet of Things holding out great promise for transformation of all current practices. As companies embrace this buzzword or react to it, it needs to be realized that this is quite a major revamp of the entire setup and not just the introduction of newer technologies. The convergence of a whole lot of innovation and their continuous adoption and further innovation is delivering an environment where efficiency is maximized over all activities and processes.

What is the basic prerequisite for Digital Transformation?

It is the involvement and integration of every component of a business operation. For Digital Transformation to really achieve its potential, every part of an organization and its staff need to be connected to the transformation as too needs to be all operations and data. The interlinking of data to feed and refine decision-making processes translates into all data becoming crucial for every decision. Insights will be gleaned from across the organization and not any more from specific departments.

Who benefits the most?

It is ultimately the customers who are going to be struck by this new approach and delivery wherein the buying experience becomes elevated to rarefied heights. To create such an outcome, the tools and the ways and means that employees have at their disposal will be radically advanced thereby making employees work better.

From Chief Information Officer to Chief Integration Officer

The times are a changing and technology is gaining rapid momentum. When one grasps the momentum of the event, it is clear that these are the times of maximum revolution in all spheres of business. Technology is bringing about a new kind of existence where there is no room for vagueness. It is all about learning and adapting. To rise to the occasion, CIOs need to be afraid of complacency.

Restructuring comes to the Enterprise

Digital Transformation is raising the bar all around the organization. All activities and processes are going to be ultra-refined and revamped beyond recognition. Leadership is crucial now and CIOs need to get on their battle gear. This is a challenging time and most importantly an exciting time. It is going to be a time where employees are going to get into the great learning evolution. Like the Ice Age and the Dark Ages, we are now entering the Age of Learning. This is going to make humans ultimately realize the great wealth of knowledge that is out there to be delved into.

Digital Transformation of Everything

It is going to be an age where humans are going to shake away their immersion into straitjackets of learning. This is going to be the age where the Learning of Everything is going to come about. An unification of all learning disciplines is the new model. And the CIO is the person making the first move in taking over the entire organization as the ambit of operation. To be afraid of this overarching venture is to be prepared fully. It is time to get down to work, to move out of the Department and into the Organization.

Artificial Intelligence in Medicine

Is Artificial Intelligence going to transform Medicine?

Artificial Intelligence in Medicine requires the collation of vast sets of data combined with detailed inputs from doctors and other medical professionals. With a steady agglomeration of data, AI can deliver the possibility of machine diagnosis of diseases and the ideal treatment regimen. Together with all of the data, algorithms can create the best models based on either rules or on inferences.

Initial Interest in the 70s

INTERNIST-1 was designed in the early 70s with a partitioning algorithm and exclusion functions. Prior attempts had been based on statistical models developed by Thomas Bayes and on Pattern Recognition. Ineffectiveness in diagnosing complex conditions led to INTERNIST-1 being redefined with the introduction of a microcomputer as Quick Medical Reference (QMR). Another system that was developed in the early 1970s was Mycine written in the Lisp programming language. Present Illness Program (PIP) and CASNET were the other systems developed in that period.

Revival in the 2000s

After a period of stagnation in the 90s, the turn of the millennium brought technology to te forefront of all business and lifestyle endeavors. This period was marked early on by the defeat of Chess World champions by computers, the victory of computers at popular games and the spread of smartphones and networked homes. Through the 2000s, processors kept getting better and better while also getting cheaper. This brought AI back onto the fast track of innovation.

Peculiar case of Medicine

In medicine, physicians and experts develop their knowledge by a process of slow and incremental learning through the years. No amount of educational brilliance can surpass a doctor who has seen and observed patients and diseases progress, retreat and be treated or overcome the bodily and chemical responses. Now with digitization and standardization, it is possible to let AI systems scour through all the electronic documents and accumulate learning and intuitions. It is but a matter of time before a well-designed system comes into the practice of diagnosis of diseases after going through each and every document that is out there in a clinic, hospital or in way-bigger systems.

Faster evaluation of test/scan results

AI systems can be trained to look into the images that are a fundamental feature of medicine today. When a system looks an image of a scan, it will have the ability to pick up the minutest patterns that are present in the image. These are jobs that usually occupy the time of the doctors and which will be freed up by relying on AI. Further, the job is not only done fast but also probably better, which makes it an ideal situation when doctors with experience are not available.

Building the system

The more wider the system that feeds into the AI machine, the better that machine learning can come up with better outcomes. When physicians train the AI system, it gets the right directions in which to drive at as it goes about bettering itself each day of its evolutionary existence. Even with the earliest systems of the 70s, it was observed that improvements are dramatic when the early errors are corrected and the system is pointed in the way to go.

Exciting and futuristic probabilities with AI

Epidemics are one of the main target areas that AI can address with great effectiveness. When it comes to handling multiple variables and analyzing them comprehensively, an AI system can help develop just-in-time alerts for healthcare systems. Another equally futuristic possibility is that of detecting when diseases are going to occur in risky sections of the population. This makes disease treatment a highly-enhanced area of medical operation wherein there is no surprise at all when a disease is found in a person.

A whole new outlook on disease

In the dramatic future that AI can deliver within this decade itself, diseases will end up being similar to greying of hair or wrinkling of skin as they are known well in advance. This can transform the very model that medicine is based upon, from that of having patients who have no clue on what is going to happen next to one where patients know about its imminent arrival and all that can be done to stave it off even before it has reared its head.