State of Health AI Industry in Singapore and IHiS'Role

State of Health AI Industry in Singapore and IHiS'Role

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No more the realm of science fiction, AI and robotics are transforming healthcare.

Today, AI is used to diagnose diseases, recommend treatments, and even perform surgeries. And hopefully, as time goes by, AI will play a much more significant role in improving patient outcomes and reducing healthcare costs.

In Singapore, the Healthcare AI industry continues to be in its nascent stages. However, several startups happen to be using AI to produce innovative solutions for the healthcare sector.
Demystifying Healthcare AI: Historical Context and the Current State of AI in Healthcare

As healthcare professionals explore the utilization of AI in healthcare, several questions and concerns have been raised. This section aims to clarify the application form of AI in healthcare and its potential implications.
The Origin of AI and its Application in Healthcare

AI has existed for centuries, having its origins tracing back once again to Greek mythology. In the tale of Pygmalion, a sculptor falls in deep love with a statue he's created. His wish is granted upon praying to the gods, and the sculpture concerns life.

The term “robot” was first found in the 1920 play RUR (Rossum's Universal Robots) by Czech writer Karel Capek. The term “robot” comes from the Czech word “robota,” this means forced labour or drudgery.

However it wasn't before 1950s that AI began to be developed as a scientific discipline. In 1956, a small grouping of researchers at Dartmouth College convened for a summer workshop to go over the likelihood of making intelligent machines. This marked the beginning of AI as an official field of study.

In early days of AI, the focus was on developing machines that could replicate human intelligence. This was called the “strong AI” approach.

However, it soon became apparent that creating machines that might think like humans was a much more difficult task than initially thought. Consequently, the focus of AI shifted to developing machines that might carry out specific tasks, referred to as the “weak AI” approach.

That's the approach that is most commonly used today. And it's why AI applications tend to be referred to as “narrow AI” or “applied AI.”
When Was Artificial Intelligence (AI) First Used in Healthcare?

AI found its way in to the healthcare industry in the first 1970s, where it was applied to biomedical problems such as cancer detection and drug development. That saw a proliferation of AI research in the medical field.

In 1980, an international AI journal called “Artificial Intelligence in Medicine” was launched. AI would be incorporated into clinical settings in the decades that followed.

In the 1990s, a renewed interest in AI was driven by computer science and machine learning advances. That resulted in the development of new AI applications in healthcare, such as for instance Fuzzy expert systems, artificial neural networks, Bayesian networks, and decision support systems.

In 2012, Geoffrey Hinton, some type of computer science professor at the University of Toronto, developed a machine-learning algorithm called “AlexNet.” That introduced the present era of “deep learning,” which includes seen an important increase in the accuracy of AI applications.

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