The State of AI 2017: Inflection Point - Healthcare

December 22, 2017

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The State of AI 2017: Inflection Point Report by MMC Ventures in associate with Numis

 

Artificial Intelligence (AI) has been described as “the ultimate breakthrough technology” (Satya Nadella, Microsoft). Five of the world’s ten most valuable companies – Alphabet (Google), Amazon, Apple, Facebook and Microsoft – are repositioning to become AI-first organisations. While the last ten years have been about building a world that is mobile-first, “in the next ten years, we will shift to a world that is AI-first.” (Sundar Pichai, Google).

 

While hype around AI is at a peak, and some expectations may exceed results in the short term, we believe AI represents a paradigm shift in technology that warrants the attention it is receiving. In 2017 AI reached an inflection point, driven by milestones in investment, capability, entrepreneurship and adoption. The implications for consumers, companies and society will be profound.

 

Our inaugural State of AI report for 2017 is intended to inform and empower corporate executives, entrepreneurs and investors. While accessible and jargon- free, it draws on new data and over 400 discussions with ecosystem participants to go beyond the hype and explain the reality of AI today, what is to come and how to take advantage. Every chapter includes actionable recommendations for executives, entrepreneurs and investors. 

 

MMC Ventures

 

Founded in 2000, MMC Ventures is a research-driven venture capital firm investing in high-growth technology businesses. MMC has backed more than 50 enterprise software and consumer internet companies that have the potential to change the future of financial services, the workplace and retail. MMC invests on behalf of private and institutional investors. MMC has over £200 million under management and is investing approximately £25 million annually. MMC’s portfolio includes: Appear Here, Bloom & Wild, CloudSense, Elder, Gousto, Interactive Investor, Masabi, NewVoiceMedia, Signal Media, SafeGuard, Sky-Futures, Small World FS and Tyres on the Drive.

 

mmcventures.com

@MMC_Ventures

 

Numis

 

Numis is the UK’s leading mid market investment bank with a focus on high growth companies both in the listed and unlisted equity markets. Numis has the no. 1 rated equity research team, the leading market share in UK equity issuance and the most UK listed corporate clients, at 200, of any investment bank. In 2015, Numis formalised its efforts in the unlisted market with the formation of its Venture Broking team and its investment in Crowdcube, the largest UK investor in seed and stage A companies.

 

numis.com

@NumisSecurities 

 

 

Healthcare industry focus

 

In the next 20 years, AI can unlock a paradigm shift in healthcare to improve patient care and process efficiency. Automated diagnosis was an early use case for rudimentary AI in the 1980s. ‘Expert systems’ mimicked human approaches to diagnosis, applying rules-based inferences to bodies of knowledge. Modern AI, particularly deep learning, is more effective and applicable to a wider range of processes. Key use cases include diagnosis, drug discovery and patient monitoring.

 

Diagnosis: Replacing complex, human-coded sets of probabilistic rules, deep learning solutions identify subtle correlations between vast, multi-variate data sets to deliver scalable, automated diagnosis. While systems are nascent, accuracy is improving rapidly. Separately, computer vision solutions powered by deep learning are transforming diagnostic imaging. While human radiologists require extensive expertise and years of training to identify abnormalities in magnetic resonance images and ultrasounds, deep learning systems trained on large data sets deliver impressive results.

In 2017, diagnostic imaging powered by deep learnings offers human-level accuracy and high speed in select contexts.

 

Drug discovery: Today’s drug discovery process is lengthy, averaging 12 years to market (California Biomedical Research Association). Expense and uncertainty are also prohibitive; drug development costs an average of $359m and just 2% of US preclinical drugs are approved for human use (ibid).

AI is being applied to multiple stages of the drug development process to accelerate time to market and reduce uncertainty. AI is being applied to synthesise information and offer hypotheses from the 10,000 research papers published daily, predict how compounds will behave from an earlier stage

of the testing process, and identify patients for clinical trials.

 

Monitoring: Monitoring the vital signs of patients on non- acute wards, or at-risk individuals in the home, remains a manual process undertaken periodically. AI can synthesise signals from inexpensive wearable devices worn by patients to deliver clinical-grade monitoring, and enable a large group of patients to be monitored in real-time by a single nurse. As data sets are amalgamated and algorithms are tuned, AI will offer predictive analytics. Patients in a ward or at home who require further hospital care can be identified and supported, while unnecessary use of hospital beds can be reduced. 

 

The applications, implications and adoption of AI 

 

Applications will be most numerous in sectors in which a large proportion of time is spent collecting and synthesising data: financial services; retail and trade; professional services; manufacturing; and healthcare. Applications of AI-powered computer vision will be particularly significant in the transport sector. 

 

AI offers new opportunities for disruption in sectors ranging from manufacturing to healthcare. Identify business processes ripe for improvement or reinvention through AI, particularly in sectors in which data synthesis or processing are extensive.

 

AI offers new opportunities for disruption in sectors ranging from manufacturing to healthcare. Identify business processes ripe for improvement or reinvention through AI, particularly in sectors in which data synthesis or processing are extensive. 

 

AI, growth of ‘x-as-a-service’ consumption, and subscription payment models will obviate select business models and offer new possibilities in sectors including transport, insurance and healthcare

 

Applications will be most numerous in sectors in which a large proportion of time is spent collecting and synthesising data: financial services, retail and trade, professional services, manufacturing and healthcare.  

 

 

In the next ten years, AI will be deployed in all sectors and to a wide variety of business processes. However, AI will have more numerous applications and greater impact in some sectors than others. AI’s impact will be greatest in sectors in which a large proportion of time is spent collecting or synthesising data, or undertaking predictable physical work. In several sectors (fig. 23), professionals spend one third or more of their time on the above (McKinsey, Julius Baer).

 

These sectors include:

Finance and insurance (50% of time)

Retail, transport and trade (40% of time)

Professional services (37% of time)

Manufacturing (33% of time)

Healthcare (33% of time) 

 

 

Use cases for AI are proliferating as understanding of the technology improves. We describe 31 core AI use cases in eight sectors: asset management, healthcare, insurance, law & compliance, manufacturing, retail, transport and utilities.

AI will have significant implications 

 

By automating capabilities previously delivered by human professionals, AI will reduce the cost and increase the scalability of services, significantly broadening participation in select markets.

 

Today, access to sectors including healthcare and financial services is limited to subsets of the global population.

 

Medical diagnosis, for example, is inaccessible to people in developing economies and expensive for those in developed nations. Diagnosis has been undertaken by experienced professionals, whose training is time consuming and whose scalability is limited, inhibiting supply and increasing cost.

 

AI will provide automated diagnosis for a growing proportion of conditions. The marginal cost of diagnosing a patient with an AI algorithm will be nil. With smartphone adoption in developing economies increasing rapidly, from 37% in 2017 to an estimated 57% by 2020 (GSMA), barriers to access are also falling rapidly. By transferring the burden of diagnosis from people to software, global access to primary care will increase. Millions of additional individuals will benefit from primary care, while the market for providers of relevant and associated technologies will expand. 

 

Benefits and risks to society 

 

AI will provide benefits to society including improved health, broader access to services and more personalised experiences. It will also present challenges and dilemmas, including issues of job displacement, bias, conflict and privacy.

 

The benefits of AI for societies will be profound and numerous. They include: broader access to better and less expensive healthcare; increased mobility and fewer accidents; broader access to lower cost legal services; increased agricultural productivity and manufacturing capability; more efficient and satisfying retail experiences; improved management of financial assets and risk; accelerated cycles of innovation; and greater day-to-day convenience. 

 

AI entrepreneurship is unevenly spread

 

More UK AI companies are addressing the marketing & advertising function (one in seven companies) than any others (fig.37). Of companies with a sector focus, finance (more than one in ten UK AI companies) and healthcare companies predominate (fig.38). 

 

 

The dynamics of UK AI: Snap40 

 

Q) How do you use AI to solve problems?

 

A) “Our goal is to protect the health of every human being by bringing clinical attention to deteriorating health at the earliest possible point. We operate in hospitals and in patients’ homes, collecting real-time data and metrics from the patient using our own monitoring device. We monitor the patient with ICU- like accuracy, but without any leads or wires - the patient can go about their day, with snap40 at their side. We then take this huge volume of data and identify the patients that require physician or nurse attention. No physician or nurse can monitor data streams from hundreds of patients - that’s where AI comes in. If we can bring medical attention to at-risk patients earlier, we can stop them deteriorating. We can enable patients to stay in their own homes, prevent the need for unnecessary hospitalisation, and save lives. By allowing physicians, nurses and healthcare providers to scale up massively the number of patients they can manage in lower acuity environments, like patients’ own homes, we also provide cost savings to providers – through fewer hospitalisations and reduced lengths of hospital stays.” 

 

 

“The impact on healthcare will be huge. With patients living longer and greater incidence of chronic disease as a result, we either have to recruit thousands more doctors and nurses or ask how we can use technology to better leverage the people we have. AI multiplies the efforts of a single physician.” (Chris McCann, Snap40). 

 

Creating value for AI in Healthcare

 

Companies that ‘disrupt’, enabling new categories of customer to use a service, have the potential to create particularly large outcomes. Companies that automate medical diagnosis, for example, can deliver primary care at low cost. By making healthcare affordable, a larger proportion of the global population can access care, growing the market of healthcare consumers. Few businesses disrupt and a business need not disrupt to be attractive. By enlarging markets, however, disruptive companies can create outsized outcomes. 

 

Read the report here:  https://www.mmcventures.com/wpcontent/documents/The_State_of_AI_2017_Inflection_Point.pdf

 

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