Examples of Artificial Intelligence (AI)—the ability for computers to replicate human cognitive abilities like reasoning and learning—have been around in some form for over 50 years. Recently, however, we have seen a number of major breakthroughs in AI, due to advances in computing power, new intelligent algorithms, and access to vast quantities of data.
As a result, AI is finding a range of new use cases across multiple industries, improving accuracy, reliability, and efficiency. There is definitely more encouragement to invest in AI, with it spanning across multiple sectors and less risks involved, as investors may be able to translate their investments from one sector to another. Some of the most exciting applications are in the field of healthcare, where AI has the potential to provide data-driven support in decision-making.
How AI works
One of AI’s greatest strengths is its ability to analyze, process and interpret large amounts of data, using patterns in that data to make predictions. It works by combining rapid processing speeds with advanced algorithms and big data. AI algorithms may be programmed in a variety of different programming languages like Python and R, and in order to operate effectively, AI requires a solid foundation of specialized hardware and software.
Programming or ‘training’ an AI is really three processes: learning, reasoning, and self-correction. In the learning phase, the AI is fed large quantities of relevant data, and rules—algorithms—are created for actioning it. A simple example might be an AI art generator, which analyses vast numbers of images in order to learn how to create its own. This is known as ‘machine learning’. The reasoning phase is all about selecting the correct algorithm(s) to reach the required outcome, and the self-correction phase is a continuous process by which the AI makes micro-adjustments to improve its performance.
Benefits of AI in healthcare
One of the biggest development areas for AI is in healthcare. AI cannot fully replace the in-person aspect of care—and is unlikely to be able to any time soon. Instead, the considerable benefits that AI can bring to the healthcare sector largely relate to the enormous patient data sets: AI has the ability to analyze this data far more accurately and quickly than a human ever could, and advanced algorithms can obtain insights from it about patient health. Some applications of this include:
· Healthcare records: One of the most ubiquitous uses of AI is in managing patient records. Research suggests that up to a third of healthcare costs relate to administrative tasks, and applications like Google Cloud’s Healthcare app are reducing this burden by making it easier for healthcare organizations to collect, store and access patient data.
· Wearables: There is a booming market in wearable healthcare tech, like smartwatches, which also harnesses the power of AI. Software analyzes biometric data to alert both users and healthcare professionals to any changes or developments. This can be used to monitor blood sugar levels for diabetes patients, and more.
· Drug discovery: AI has been used in the discovery and development of new drugs including COVID-19 treatments.
· Treatment recommendation: Technology from IBM Watson uses AI to pinpoint specific treatments for cancer patients.
AI’s task automation and data processing has proven value in terms of error reduction and, therefore, improved clinical quality and consequent medical outcomes for patients. Researchers have even developed an AI system which can recognize a cardiac arrest during an emergency call with greater accuracy and speed than human responders! Furthermore, there is evidence that it results in better patient engagement—and of course, it makes life easier for medical professionals.
Some of the most exciting applications of AI in healthcare, however, are related to developing and encouraging preventative medicine. AI itself has made huge strides with its investments exploding in recent years. Investing in it for the long run can be quite beneficial and would further allow the use of AI, as a preventative medicine method, to prosper and grow substantially.
The role of AI in early disease detection
Primary prevention, which means encouraging healthier lifestyles through diet, exercise, is cost-effective and therefore many governments worldwide have adopted it as part of healthcare policy. Secondary prevention, however, which is screening and early disease detection to reduce rates of mortality, is lacking, in part due to the financial and human resources required. Most diseases are treated more effectively and have better outcomes when detection is made earlier, but all too often diseases aren’t recognized until they are in advanced stages, when treatment is more difficult and less successful. AI can provide assistance in two ways.
Visits to a doctor are usually short and infrequent, and by necessity focus on statistical probability rather than an individual’s risk profile. As a result, they are unlikely to pick up on underlying diseases or medical conditions. AI can provide accurate ‘first-level screening’—in other words, small changes which may indicate hidden issues.
Secondly, research has demonstrated that AI can be incredibly effective in detecting serious illness and major diseases. For example, during a 2017 study of people at risk of stroke, patients’ symptoms and genetic history were fed into an AI algorithm, which provided accurate prognosis at an early stage with 87.6% accuracy, allowing for preventative treatments. There has also been research into the ability of AI to detect lung cancer, where a UK study demonstrated that AI was able to find tumors from scans of patients’ lungs with more accuracy than medical professionals—an incredible accuracy of 94%.
By combining first-level screening and advanced disease detection, AI technology offers improved chances of early diagnosis, and therefore effective treatment. This goes hand in hand with increased investments leading to more resources for companies to work with, potentially speeding the process of improving AI in these areas.
AI: A Sound Investment for Reducing Costs and Improving Lives
The three top causes of death worldwide are cardiovascular disease, respiratory diseases, and cancers. These diseases combined require a huge amount of time, effort and resources from healthcare systems around the world, and this burden is increasing all the time. Investing in early detection and diagnosis, therefore, is crucial in reducing their impact, and healthcare organizations are increasingly looking to technological ways to save both time and money. Many companies have begun investing in AI, with massive brands spearheading the sector. Predictions for the AI market size have been set at around $390.9 Billion by 2025, encouraging investors to invest in AI, reducing the risks that may be present.
Most importantly, of course, preventative healthcare plays a vital role in improving patient outcomes, allowing them to live longer, healthier lives. Regular examinations and screenings from medical professionals will always be key in helping to detect diseases as soon as possible in their development, but by improving accuracy and efficiency, AI can provide a big helping hand.
James Ahern is the founder of Laidlaw Venture Partners and managing partner of Laidlaw & Company UK. With over 15 years of expertise in capital formation, investment banking, and equity capital markets, Ahern has partnered with innovation labs across numerous academic institutions to cultivate multiple companies now within Laidlaw’s portfolio.