The history and importance of AI in our medical sector

The first AI were focused on making decisions and abilities humans could already make, such as robotic arms or chatterbots. In this early period a important job was done, digitising data set the foundation of future utilisation within medicine and the creation of a web-based search engine built around medicine. This led to a later acceleration of biomedicine due to this large amount of data being easily accessible for not only humans but the artificial intelligence to come.

During this time we come across what is known as the first ‘AI winter’. This is when AI projects had investment defunded and the interest in it dropped. This was due to a number of factors but one of the most important is the limited computer power available. However it is worth noting there were some advancements made within this time period: In 1973 a time shared computer system was created which enhanced communication for biomedical institutions that meant that advancements and information could be done efficiently. One of the first consultation programs was made during this time using the CASNET model. This model could apply information about a specific disease and provide doctors information on how they could treat them. To build on from this another system was built in 1986 called DXplain, another decision support system conceived by the University of Massachusetts. This program could take information about specific diseases and apply them to around 500 diseases and then up to 2400. When we hit the 1990s we found interest in Machine learning was renewed and the medical world set the stage for modern ML.

Now we reach the modern age where AI runs the headlines with chat gpt disrupting many sectors. One of the sectors AI is shaking up is medicine where AI has become a tool to carry us to an increase in lifespan.
The examples of how this is done is shown below:

Although some may say that the overall progression of technology into the future is a bad thing, the asset that computer science has provided to the medical industry cannot go unnoticed. We have seen advancements in diagnosis technology being able to locate rare diseases patients may have saving lives quickly. This goes hand in hand with AI ability to personalise treatment for patients. This has meant that we can optimise the lifespan of the human race and in turn improve our living conditions. As we look to the future we may find that AI becomes a tool as common as the calculator and with this change we may find health sectors becoming a higher standard for us.