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tmcapital/healthcare
The Next Generation of Medicine:
Artifcial Intelligence and Machine Learning
TM Capital
Industry Spotlight
tmcapital/healthcare
Case Study: Growth Equity Capital Raise
Analytics 4 Life raised $25.6 million through the sale of
Series B Convertible Preferred Stock
Analytics 4 Life, a Toronto-based developer of artificial
intelligence-enabled medical imaging solutions, has raised
$25.6 million through the sale of Series B Convertible
Preferred Stock. Analytics 4 Life, led by former Sapheon,
Inc. CEO Don Crawford, is focused on using artificial
intelligence to improve, simplify and reduce the cost of
diagnosing coronary artery disease (“CAD”), a $6 billion
global market. The Company’s non-invasive medical
device, CorVista, applies machine learned solutions to
assess the presence of significant CAD, using
physiological signals naturally emitted by the body.
Beyond CAD, Analytics 4 Life has begun to apply its
proprietary signal processing and artificial intelligence
platform to developing new products that address other
cardiac conditions and disease states in neurology and
oncology.
TM Capital served as financial advisor to Analytics 4
Life in connection with this transaction. The Company
plans to use the proceeds to complete the final stage of
testing and apply for FDA approval. In addition, the
financing will enable Analytics 4 Life to build the necessary
team to bring this potentially transformative diagnostic
solution to a wide audience of physicians and patients.淘宝店铺
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tmcapital/healthcaretmcapital/healthcare
Introduction
Artificial Intelligence (“AI”) applications, powered by an influx of big data and advancements in computing power, are
positioned to transform major sectors, while simultaneously creating new industries. AI is expected to contribute up to $15.7
trillion to global GDP by 2030.1
The AI industry has the capability to not only augment and improve, but also to replace many tasks that have been
historically executed by humans. Simultaneously, AI will create many new jobs that are yet to be identified.According to
the U.S. Department of Labor, “65% of the school children [in 2016] will be eventually employed in jobs that have yet to be
created.”New technologies and innovations in AI will transform most consumer, enterprise and government markets around
the world. However, the commercial uses for AI applications are still nascent and ripe for investment. As such, the industry
is attracting strong interest from a broad range of investors.
This report will review the important role that AI plays in healthcare, but first we will summarize the definition of AI and its
evolution to date.
Defining Artificial Intelligence and Machine Learning
AI refers to multiple technologies that can be combined in
different ways to sense, comprehend and act with the
ability to learn from experience and adapt over time (See
Figure 1). In basic terms, AI is a broad area of computer
science that makes machines and computer programs
capable of problem solving and learning, like a human
brain. AI includes Natural Language Processing (“NLP”)
and translation, pattern recognition, visual perception and
decision making. Machine Learning (“ML”), one of the most
exciting areas of AI, involves the development of
computational approaches to automatically make sense of
data – this technology leverages the insight that learning is
a dynamic process, made possible through examples and
experiences as opposed to pre-defined rules. Like a
human, a machine can retain information and becomes
smarter over time. Unlike a human, a machine is not
susceptible to sleep deprivation, distractions, information
overload and short-term memory loss – that is where this
powerful technology becomes exciting.
The Evolution of AI and ML
AI is not a new concept – in fact, much of its theoretical and technological underpinning was developed over the past 60
years. Although AI has been a part of our day-to-day lives for some time, this technology is at an inflection point, largely
due to major recent advances in deep learning applications. Deep learning is a sub-set of ML that utilizes networks which
are capable of unsupervised learning from data that is unstructured or unlabeled. The neural networks that underpin deep
learning capabilities are becoming more efficient and accurate due to two significant recent technological advancements:
an unprecedented access to big data and an increase in computing power.The effectiveness of neural networks correlates
1 PwC, “AI to drive GDP gains of $15.7 trillion with productivity, personalisation improvements” (June 27, 2017)
Figure 1: What is AI and ML
The AI industry – encompassing a broad set of information systems inspired by human learning and
reasoning systems – is a $2.4 billion market that is expected to grow dramatically to over $59 billion
by 2025. The Healthcare AI market, among the AI industry’s fastest growing sub-sectors, is expected
to grow at a 39.4% CAGR to over $10 billion in worldwide revenue by 2024.
Artificial Intelligence refers to multiple
technologies that can be combined to:
AI
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ActSense
Machine
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Language
Processing
Computer
Vision
Expert
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Knowledge
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Audio
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Comprehend
Source: Accenture, “Why is AI The Future of Growth” (2016).。。。以上简介无排版格式,详细内容请下载查看