Among remarkable developments in Artificial Intelligence (AI) and Machine Learning (ML) over the last couple of years is an increase in startups that have attracted massive funding and backing from some of the world’s leading corporations and individual investors. Influential organizations including Google, Facebook and Intel have thrown themselves headfirst into the development of AI/ML tools, products and projects. This underlines the importance of Artificial Intelligence (AI) and Machine Learning(ML) in shaping the way products and services are developed and delivered in enhancing the quality of life.
Artificial Intelligence is the larger body under which ML and Deep Learning (DL) technologies fall. These growing technologies are often discussed and used interchangeably, although their application is relatively varied. The healthcare sector has been a major beneficiary of AI/ML/DL developments, helping to redefine how health services are accessed, assessed and provided. After an indisputably difficult experimental period- characterized by several false starts- AI/ML is starting to make an enviable forward thrust. This discussion interrogates two fundamental questions: (i)How much investment is going into healthcare-related AI/M projects? (ii) Is this investment and effort worthwhile and how will it help to improve the field of medicine in general and cancer treatment in particular?
Investment in Healthcare-Related AI/ML related projects.
Considering the dynamics and frequent turnabouts, it is not easy to precisely quantify investment into AI/ML projects. However, capital injection in related projects is evidently on the rise. New York-based bank TM Capital indicated that startups with a focus on AI/ML healthcare technology raised up to $690 million in 2017. In 2016, $794 million was invested across 90 deals related to healthcare AI technologies. Overall, more than $5bn has been raised by AI/ML startups since 2012. Venture Capital(VC) deals that successfully closed between 2012-2016 rose from 20 to about 70, a trend that is likely to gain momentum in coming days.
It is also projected that over $20bn will be invested in AI/ML healthcare technologies by mid-2020s. Towards the end of 2017, Microsoft announced a $3.5 million competition for AI startups. Through Microsoft Ventures, the tech giant reported that it had invested in over forty outstanding AI innovators including Livongo, a healthcare startup that is using advanced analytics to drive change in the management of chronic diseases.
Deep Genomics, a company that aims to bring to the world life-saving genetic therapies, announced in September 2017 that it had received a $13 million equity investment from VCs such as Khosla Ventures.
In 2014, Google acquired British-based AI startup DeepMind for approximately $500 million. Through DeepMind Health, the company is already leveraging AI tech to help deliver fast and more efficient information to help save lives. Among its debut products is the Streams App, able to send upfront alerts to healthcare providers if a patient’s status deteriorates. Although DeepMind has reportedly made heavy losses through hefty legal fees and research projects, parent company Google is still willing to explore all options to realize its full potential. Google’s Developer Relations Program Manager Malika Cantor asserts this commitment saying that AI and ML are part and parcel of the company’s drive to solve the greatest challenges facing humanity. With CEO Sundar Picahi emphasizing that Google’s future will be based on Artificial Intelligence, there is no doubt that more investment in AI/ML will be forthcoming.
Is the effort worth it and how will it help to improve the field of medicine?
The fact that companies and individual investors are willing to stake so much money in these technologies rubber-stamps the potential they harbor. This is further affirmed by the encouraging trend where most of the companies (especially in healthcare development), are young startups and/or affiliates and subsidiaries of mega-corporations.
An underlying mission for these companies is that they want to change the overall approach to healthcare problems and solution finding. This mankind-first approach makes their effort more important than any amount of money that can ever be invested in them.
Recently, Oregon State University researchers were able to simplify the classification of breast cancer cells using Deep Learning technologies. The process, known as gene expression data, is one of the many highly complex diagnostic procedures in cancer treatment. A great step forward.
Atomwise, a startup based in San Francisco is developing super computers aimed at enhancing drug development processes in a bid to replace test tubes. In drug making, testing of cell type, genetic combinations and other biological processes consume a lot of time. On average, drugs take 12-14 years to be fully ready for market. Speeding up this process will boost efficiency and save time. Progress.
A Chinese team of researchers has also used deep learning to set apart benign and malignant breast tumors with a 93% accuracy in procedures performed on over 200 patients. The cancer threat is a leading headache for the whole world. Such achievement is simply awesome.
Where does all this lead to?
The benefits of AI/ML and Deep Learning in the field of medicine has unlimited potential in revolutionalizing the industry. From medicine manufacturing to specific and specialized tasks, such as imaging and oncology, artificial intelligence is and will continue to be an important component. Pushing aside the profit aspect of the business, companies that have stepped into this field have almost unanimously stated their commitment to finding solutions to some of the world’s most enigmatic health problems.