Big data and traditional Chinese medicine (TCM): What’s state of the art?

Abstract

Big data and traditional Chinese medicine (TCM) is a new interdisciplinary field quietly emerging in Chinese society. Internet of Things (IoT) sensor system technology is currently being developed to gather large volumes of personal data so that TCM, specifically herbal pharmaceutics, can be applied to treat acute and chronic diseases alike utilizing low cost, safe, and effective treatment protocols that have been prescribed in clinical practice for thousands of years. Through a survey of existing literature, this paper investigates what a future state of medicine may look like with the deployment of a big data TCM system as a means to enhance humankind’s health and quality of life.

Full text

978-1-7281-0858-2/19/$31.00 © 2019 IEEE
Big data and traditional Chinese medicine (TCM):
What’s state of the art?
David C. Mainenti
Palmer iSchool of Library and Information Science
Long Island University
Brookville, NY 11548
Email: david.mainenti@liu.edu
Abstract—Big data and traditional Chinese medicine (TCM) is
a new interdisciplinary field quietly emerging in Chinese society.
Internet of Things (IoT) sensor system technology is currently
being developed to gather large volumes of personal data so that
TCM, specifically herbal pharmaceutics, can be applied to treat
acute and chronic diseases alike utilizing low cost, safe, and
effective treatment protocols that have been prescribed in clinical
practice for thousands of years. Through a survey of existing
literature, this paper investigates what a future state of medicine
may look like with the deployment of a big data TCM system as a
means to enhance humankind’s health and quality of life.
Keywords—clinical diagnosis, cultural medicine, herbal
pharmaceutical technology, Internet of Things (IoT), sensor systems
and applications
I. INTRODUCTION
Since the earliest of known times, Chinese civilization has
existed in a state of culture sophisticated enough to have
developed a system of natural living and well-being aimed at
interpreting, though by theories devoid of even the most primary
Western scientific elements, the construction of the entire
universe, including all of its phenomena and mysteries [1]. For
thousands of years, information collected by practitioners of
traditional Chinese medicine (TCM)
1
has been considered
comprehensive data, reflecting the state of health of all human
beings in relation to their environment, nature, earth, and the
heavens [2]. While Western medicine has made great scientific
contributions from a micro perspective [3], it at times fails to
recognize many complexities in the body at the macro level [4];
enter TCM, whose real-world clinical research paradigm is
human-centered, data-oriented, and problem-driven, seamlessly
weaving medical training with academic computations and
clinical practice through the utilization of non-invasive,
painless, and inexpensive protocols [5]. Specifically, TCM may
be studied and applied by extracting quintessential information
from complex and redundant data utilizing Chinese medical
principles, intelligence, data, and computing sciences;
interactions between a potentially unlimited number of internal
and external human factors and their relationship to etiology,
pathogenesis, disease location, biology, and complex states can
thus be explored using big data through a comprehensive
treatment perspective that maintains its harmony with nature [6].
1
TCM is a form of cultural medicine that utilizes various protocols, including
acupuncture, moxibustion, herbal medicine, massage, exercise, and dietary
therapy, to bring the body’s vital energy or “qi” to a state of equilibrium and
balance. To date, scientific research has not found evidence for many TCM
The purpose of this study is to provide an overview of big
data (particularly in relation to healthcare and clinical medicine)
and survey the state of the art in this new interdisciplinary field.
A literature review was conducted to identify pertinent studies
using a combination of specific keywords to isolate publications
of interest. Studies examining big data and TCM were then
reviewed and categorized into five research themes for further
analysis. Results illustrate the potential of big data to become a
common feature of TCM, acting to modernize this classical
system in so far as to create a future state of medicine that could
help eradicate many acute and chronic diseases prevalent in our
global society today.
II. LITERATURE REVIEW
The dawn of big data arrived in the 21st century when two
leading scientific journals, Nature and Science, created special
issues to discuss its potential impact on society for future
generations [7]. According to a recent report [8], in 2018 more
than five billion consumers interacted with data on a daily basis;
by 2025, that number will exceed six billion individuals using
Internet of Things (IoT) devices connected worldwide that are
expected to create over 90 zettabytes (90 trillion gigabytes) of
data. As a result, business intelligence, through the utilization of
big data, has become a major technological trend in the current
decade [9]; in fact, at least 97 percent of companies with
revenues exceeding $100 million were found to employ some
type of corporate analytics [10]. Big data is now amassed by
many disciplines, made possible by ubiquitous, information-
sensing devices and software [11]. Google, Amazon, and
Facebook regularly harness big data on the web and, in the
process, have revolutionized how to sell advertising, causing
some to claim data has become a new class of economic asset,
similar to currency or gold [12]. On the horizon, new hardware
paradigms are moving beyond digital and silicon to analog and
carbon nanotubes with hybrid chips, sensors, and 5G antennas,
disaggregating the clouds of concentrated computing and
commerce, moving information to the sky – rendered on each
user’s laptop and smartphone, spread across blockchains,
transparent and transformative [13]. In the classical DIKW
hierarchy, the first two layers can now be expertly excavated and
warehoused incessantly, moving towards intelligent and
actionable knowledge and, ultimately, wisdom, based on hidden
concepts, theories, diagnostic techniques, and practices, due in part to patient-
centered methodological and logistical issues associated with randomized
controlled trials. Further, disagreement oftentimes exists among practitioners
on how such medical modalities should be selected and/or delivered.

patterns identified through data mining as gleaned by experts,
decision makers, and artificial intelligence, resulting in new
professions that laid roots over seventy years ago [14].
In particular, the healthcare industry is facing a tsunami of
health-related content generated from numerous patient points
of contact, sophisticated medical instruments, wearable devices,
and web-based communities [15]. In fact, major initiatives seek
to address fundamental technical and scientific issues that would
transform treatments from reactive and hospital-centered to
preventive, proactive, evidence-based, and person-centered
using sensor technology, networking, information, and machine
learning [16]. As a result, big data-based processing and analysis
platforms have been proposed for practitioners, specialists, and
clinicians that combine technologies with relevant standards
such as treatment and intervention guidelines, user needs, and
issues surrounding scattered medical information and
insufficient information mining, all designed to maximize
protocol results, provide the basis for scientific research and
clinical practice, ensure medical quality and safety, enhance the
overall quality of medical services, improve access to
healthcare, reduce healthcare costs, and decrease medical risk
[17]. Additionally, to improve medical services to patients
worldwide, blockchain and tokenization technologies are
starting to gain momentum so that readily available, centralized,
and standardized medical record histories can be accessed
anywhere and at any time [18].
Advances in big data processing for health informatics,
bioinformatics, sensing, and imaging may have a great impact
on future clinical research, even with its risks and challenges;
solely consisting of personal data, which has been regarded as
the “new oil” of the 21st century, medical data will reach
zettabyte (10
21
) and yottabyte (10
24
) levels for countries with
large populations, including emerging economies such as China
and India [19]. Huh [20] determined that if big data is collected,
processed, and analyzed using various techniques, it is expected
to be able to prevent and treat various diseases, including
obesity. There is clearly much to learn from datafying how one’s
body works; in time, this process may rival the printing press by
providing humankind with the means to map our entire world in
a quantifiable and analyzable way [21]. Health informatics thus
appears here to stay, as the growing pervasiveness of the IoT is
contributing to an increased appreciation of data as a valued
asset, with data scientists taking the initiative to shape the way
we live, work, and play in tomorrow’s world [22]. As healthcare
institutions recognize data as a corporate asset and promote data-
driven cultures, it may be wise to consider employing aspects of
a traditional system of cultural medicine that has, at its core,
effectively utilized big data elements for thousands of years but
yet, to this day, remains a mystery to the scientific community.
III. MATERIALS AND METHODS
A literature review was conducted to identify studies on big
data and TCM. Scopus® (www.scopus.com), considered by
some to be the largest abstract and citation database of peer-
reviewed literature, including scientific journals, books and
conference proceedings, was initially searched on October 30,
2018 for all citations with the string [“big data” AND
“traditional Chinese medicine”]. The results of the search
revealed forty six (46) documents for the period 1935-2018, all
published within the last five years. One citation was removed
as it represented a summary of IEEE conference proceedings.
Individual document abstracts were gathered for content
analysis; each was reviewed and coded into a major theme,
based on the overall purpose of the referenced work.
IV. RESULTS
Forty five documents referencing big data and TCM were
coded into five broad research themes, based on their published
abstracts (see Fig. 1 for results). Half of the documents were
conference papers, supporting the idea that this research front is
just emerging in society. Twenty percent of the documents were
written in Chinese and all major affiliations were institutions
located in China. Further, when investigating countries of
publication origin presented in Fig. 2, forty-four of the
documents originated from China. Subject areas of published
works on big data and TCM are illustrated in Fig. 3; the three
largest include computer science, medicine, and engineering.
This broad subject range indicates big data and TCM could
potentially influence a number of scientifically related domains
and research areas, particularly in China. A review of each
document follows in the sections below, with works presented
in chronological order by year within each theme.
Fig. 1. Research Themes, Big Data and TCM. (Scopus)
Fig. 2. Publication Country of Origin, Big Data and TCM. (Scopus)
Fig. 3. Subject Areas, Big Data and TCM. (Scopus)
TCM Big Data
Framework; 46%
IoT Sensor
Technology; 22%
Treatment of Specific
Diseases; 13%
Pharmaceutics and
Herbal Medicine; 13%
Other Research; 6%
China
88%
United States
4%
Canada
2%
Hong Kong
2%
Macao
2%
Undefined
2%
Other
12%
0 5 10 15 20 25
Computer Science
Medicine
Engineering
Pharmacology, Toxicology and…
Social Sciences
Decision Sciences
Biochemistry, Genetics and Molecular…
Materials Science
Energy
Health Professions
Mathematics
Physics and Astronomy
Business, Management and Accounting
Chemical Engineering
Earth and Planetary Sciences
Number of Publications

A. TCM Big Data Framework
Wang & Chen [23] first discussed how the TCM method of
diagnosis based on syndrome differentiation
could, in this new
era of big data, work on a molecular basis and be analyzed using
multiple “omics” technologies. Zhang & Zhang [24] proposed a
systematic framework involving the creation of a data platform,
implementation of data analysis technology, and training of big
data professionals to eliminate previous defects and weaknesses
associated with TCM and sampling, shifting the medicine into
the fourth paradigm of science where correlation replaces
causality. Cui et al. [2] determined that the development of TCM
informatics, using long-term genetic and natural information,
could be inevitable and that methods and techniques should be
provided to process and analyze TCM as comprehensive data.
Liu [25] discussed the massive digitization efforts of TCM by
the China Academy of Chinese Medical Science (the most cited
affiliation in this study) and charts three future pathways to
improve healthcare worldwide: 1) construct a national center for
TCM data that includes data sharing mechanisms, data on
critical and life threatening diseases, and aggregated data from
diagnoses, treatments, and clinical studies; 2) develop IoT
devices that enhance the ability to collect massive TCM data;
and 3) create a scalable system that securely digitizes, collects,
and utilizes data resources from innumerable sources, including
both classical and modern literature. Li et al. [6] projected using
big data to transform TCM qualitative data into quantitative
statistical values that could be analyzed by complex networks
that model and recommend individualized TCM treatment
modalities. Song et al. [26] proposed the formation of a new
comprehensive modality for TCM pedagogy using modern big
data approaches. Feng et al. [27] developed an annotation
system for TCM clinical text corpus in Java to reduce manual
labor by implementing both supervised and unsupervised
machine learning, along with structured data comparison, to
assist with the management of clinical records. Additionally,
Song et al. [28] developed a clinical research sharing system for
TCM using structured electronic medical records as the
technology platform for clinical diagnosis and treatment
information, laying the groundwork for further research on TCM
data using both statistical analyses and data mining.
Because of the sheer variability of TCM data (multiple
clinical record sources, numerous symptom descriptions, many
collected clinical symptoms, more than one syndrome attached
to a clinical record, etc.), Fei et al. [29] delineated new methods
in machine learning to meet existing challenges. Honglan et al.
[30] proposed that conditional random fields be applied to
identify TCM medical record information, due to the fact that
core ideas of highly revered physicians in Chinese history
remain stored in the form of natural language. Using 500 marked
TCM medical records, they successfully identified symptoms
and pathogenesis entities in over 80% of the cases, an important
feature when creating expert system algorithms to analyze TCM
big data. Zuo [31] noted that fuzzy mathematics should be
applied to the translation of Chinese medical information so that
flexibility exists between instructional and translation strategies.
Liu et al. [32] constructed a disease-syndrome-method-
prescription-herb knowledge base model that promotes big data
mining and TCM precision. Gong et al. [33] also suggested the
establishment of a quantitative classification system for
recording symptoms, adding elements such as light degree,
medium degree, and high degree, or using a scoring system
based on criteria developed either through a Delphi study with
industry leaders or via a fuzzy mathematics model. Finally,
Ming et al. [34] outlined the creation of a comprehensive digital
Chinese medicine system, postulating the big data era can bring
great change to both society and the development of TCM,
reshaping the pharmaceutical industry and promoting the
integration of TCM with modern science and technology.
Huang & Zhang [35] documented five aspects of TCM
digitization efforts, including: the overall progress of the survey,
collection and complication of core indicators, development of
database software systems, national planning and
implementation supported by big data, and the study of single
species. Guo et al. [36] proposed a smart service framework,
using IoT devices to conduct machine learning and make
judgements regarding the treatment of various disorders based
on TCM big data. Shi et al. [37] postulated that big data
technology brings a wealth of new research opportunities, given
the characteristics and complexity of TCM, and proposed a pilot
implementation at several TCM hospitals in China. Wang [38]
outlined the design and construction of a large TCM data
platform, particularly for clinical diagnostic and herbal
prescription purposes, by digitizing the results of classical TCM
manuscripts using standard nomenclature so information can be
mined by complex algorithms. Lin et al. [39] also discussed
challenges with TCM innovation, standardization, and building
a successful big data platform. Finally, Liang et al. [40]
constructed a data representation and management approach
using true characteristics to solve issues relating to the
uncertainty of data object attributes and the non-uniformity of
information by employing modeless properties of stored objects
and hybrid indexing; results demonstrated that such a strategy
could effectively solve storage problems while also providing
satisfactory performance in query efficiency, completeness, and
robustness.
B. IoT Sensor Technology
Chen et al. [41] introduced the idea that in the future,
individuals may be able to diagnose and cure disease by
themselves via wearable sensor technology that uninterruptedly
collects and transmits personal TCM data, rendering doctors and
hospitals obsolete by using algorithms of ancient medical
practices that are inexpensive and produce few side effects. Dai
et al. [42] presented a clustering algorithm using human
monitoring technology to identify new representative health
states based on general and overarching categorical levels. Shi
et al. [43] discussed pulse diagnostic information obtained by
TCM practitioners and noted new opportunities exist in the
relationship between the human body and medicine through the
application of modern big data processing technology. Dai et al.
[44] proposed a framework to directly map images, audios, text,
and other sensory data into a computer assistant trained in TCM
diagnostic methods to manage human health states using deep
learning that fuses huge volumes of data into effective
representations. Parcus et al. [45] introduced a new mobile
phone-based image acquisition method, using a phone’s flash
and back camera, to collect tongue images with automatic white
balance for diagnostic purposes. Fu et al. [46] discussed the
challenging aspects of capturing the nature of a tongue’s
coating; they proposed using neural networks that combine the

characteristics of basic image processing and deep learning,
based on a standard and balanced tongue image dataset. Hou et
al. [47] also proposed a method to combine deep learning with a
classification system that recognizes tongue color with a high
accuracy, which is essential for effective tongue diagnosis in a
new era of big data. Zhang et al. [48] constructed an auxiliary
pulse sensor management system consisting of acquisition
equipment, software, and an Android app for daily TCM data
management via mobile terminals. Similarly, Chu et al. [49]
utilized a self-powered pulse detection sensor to measure
waveforms as a means of diagnosing irregular heartbeats using
TCM models. Finally, Chen & Wu [50] put forward a secure and
scalable method, utilizing the Hadoop distributed computing
system, to collect, store, and analyze the clinical data elements
of tongue diagnosis.
C. Pharmaceutics and Herbal Medicine
Li et al. [57] highlighted the benefits of implementing a data
integration and management system for herbal medical plants to
easily collect, integrate, store, analyze, communicate, and
visualize information in a way that helps improve performance.
Wang et al. [58] applied an algorithm to exploit and analyze
clinical data about lung cancer, with results illustrating herbal
selections that would mirror those chosen by an experienced
TCM practitioner. Zhang & Shao [59] discussed how network
pharmacology, which explores holistic correlations between
drugs and complex diseases (resulting in a paradigm shift from
one drug, one target to network targets), could be combined
with TCM to create a new comprehensive pharmaceutical
system. Bai et al. [60] offered an evaluation basis for the
effectiveness, safety, and legality of herbal preparations by
selecting appropriate DNA biomarkers, as well as applying
large-scale sequence comparisons and data mining with a focus
on biological ingredients. Zhang [61] put the international
community on notice regarding the prevalence of chronic
disease in society and challenged the pharmaceutical and
medical industries to develop new drugs with improved efficacy
and reduced side effects; citing relevant research related to
disease causality in relation to gut microflora, the author
suggested a systematic TCM data analysis be performed on the
challenges associated with new drug development and existing
drug use, particularly in cases of chronic obesity and diabetes.
Finally, Gong et al. [62] proposed a five part approach for the
secondary development of patent herbal remedies, including
implementing a continuous improvement model for herbal
control strategies based on industry big data.
D. Treatment of Specific Diseases
The first paper on treating a specific disease with big data
and TCM was written by Li et al. [51]; in this monumental work,
general and TCM information from patients diagnosed with
coronary heart disease at seventeen hospitals in China was
collected and analyzed. Results showed that approximately 80%
of all patients included in the study had a common TCM
syndrome element and were being treated with herbal remedies
for their condition along with Western medical drugs. Zhao et
al. [52] introduced a data mining technique for analyzing AIDS
syndrome classifications that eliminated three weaknesses in
previous research so as to effectively exploit latent relationships
between syndromes and symptoms. Similarly, Shen et al. [53]
used Hepatitis B disease data to show TCM big data could be a
more quantifiable and objective system of medicine than other
protocols that could be employed to diagnose and treat many
types of diseases in their earliest stages. Dang et al. [54]
investigated the use of a compound extracted from a traditional
medicinal substance (Venenum Bufonis), to explore the potential
mechanism of this remedy in the treatment of breast cancer
using the Kyoto Encyclopedia of Genes and Genomes pathway,
gene ontology enrichment, and protein-protein interaction
analysis. Yang et al. [55] found that the combined use of Chinese
and Western medicines was consistent with dynamic space-time
theory and that multiple, multidimensional, and dynamic
medicine group treatment modules could be deployed
electronically to better manage acute ischemic stroke patient
recoveries. Finally, Li et al. [56] compared several algorithms
and constructed a classification model that developed rules for
the diagnosis of hypertension in TCM, which could eventually
contribute to the standardization of the medicine as a whole.
E. Other Research
Zou & Laubichler [63] took a big data approach to explain
how China became second in the number of publications on
systems biology, with one salient difference as compared to
Western countries being that TCM was an important research
topic. On a metaphysical level, Shi & Chen [64] explored
cosmological relationships to determine if medical protocols in
a big data environment should be influenced by time of year and
geographic location. Finally, Tang et al. [65] evaluated online to
offline (O2O) catering and proposed a decision support system
for dietary recommendations based on TCM theory.
V. DISCUSSIO N
Industry has predicted that by 2060, sensors will be
embedded all around us, monitoring our health in a continuous
manner, linked to one giant AI network, acting as a virtual
doctor and directing future medical research [66]. Based on
published research to date, the era of big data ushers in the
potential for great change in both society and healthcare,
particularly with respect to the integration of TCM and herbal
pharmaceutics with modern science and technology. Table I
summarizes the major research subthemes noted in this study,
based on their prevalence within each indexed abstract.
TABLE I. M
AJOR
R
ESEARCH
S
UBTHEMES
,
B
IG
D
ATA AND
TCM
Theme Subtheme %
Treatment
of Specific
Diseases
Study the benefits of big data and TCM in the
treatment of AIDS, acute ischemic stroke, breast
cancer, coronary heart disease, diabetes, hepatitis
B, hypertension, irregular heartbeat, lung cancer,
and obesity
17.8
IoT Sensor
Technology
Develop new mobile diagnostic capture systems to
uninterruptedly collect and transmit pulse
measurements, tongue imaging, and other personal
sensory data used in TCM diagnosis
15.6
Big Data
TCM
Framework
Collect, translate, and digitize all existing cultural
and clinical TCM resources using standardized
language, machine learning, and a unified ontology
15.6
Create a national TCM data platform and IoT
resource sharing system integrated with clinicians
and hospitals
13.4
Integrate with modern science and technology by
combining TCM and pharmaceutical knowledge
with biomedical, genetic, and molecular
information
11.1

Future research appears to point towards the development of
a comprehensive design plan, using big data, TCM, machine
learning, and artificial intelligence, with a goal to improve
medical outcomes and reduce healthcare costs for society as a
whole. By investigating the convergence of factors that shape
patterns of health and disease, along with patient TCM data,
genetic, and molecular information, a new era of preemptive
medicine, specifically tailored to each human being, may begin
to take shape by employing proactive interventions and
recommendations occurring routinely through mobile devices to
reduce disease occurrence. Such a system has the potential to
accelerate and/or revolutionize new and creative scientific
solutions for both acute and chronic diseases alike.
VI. CONCLUSION
The author surveyed bibliographic information obtained
from Scopus during the past five years to evaluate what is state
of the art in big data and TCM. The results depict an emerging
research front in the development of a big data TCM framework,
using IoT sensor technology, to collect health informatics from
humans worldwide as a means to develop low-cost, minimally
invasive, and safe herbal protocols and other holistic
recommendations for both general and specific disease models.
This study helps reveal the intellectual landscape and highlights
emerging topics and trends. Additional work should be
undertaken to ensure the benefits of big data and TCM are
extended to all who can prosper from its innovative methods of
disease treatment, contributing to the health and well-being of
the earth and its inhabitants for generations to come.
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