With the growth and popularity of the utilization of artificial intelligence (AI) in several fields and industries, studies in the field of medicine have begun to implement its capabilities in handling and analyzing data to telemedicine. With the challenges in the implementation of telemedicine, there has been a need to expand its capabilities and improve procedures to be specialized to solve specific problems. The versatility and flexibility of both AI and telemedicine gave the endless possibilities for development and these can be seen in the literature reviewed in this paper. The trends in the development of the utilization of this technology can be classified in to four: patient monitoring, healthcare information technology, intelligent assistance diagnosis, and information analysis collaboration. Each trend will be discussed and presented with examples of recent literature and the problems they aim to address. Related references will also be tabulated and categorized to see the future and potential of this current trend in telemedicine.

1.
P.
Fernandez-Marcelo
, “
Telehealth and eMedicine
,”
Presentation, National Telehealth Center
,
2013
.
2.
E.
Dinya
and
T.
Tóth
, “
Health Informatics: eHEALTH and TELEMEDICINE
,”
Presentation, Semmelweis University Institute of Health Informatics
,
2013
.
3.
World Health Organization
, “2010 Opportunities and developments Report on the second global survey on eHealth Global Observatory for eHealth series-Volume 2 TELEMEDICINE in Member States WHO Library Cataloguing-in-Publication Data,” Report,
WHO Press
,
2010
.
4.
C. S.
Pattichis
,
E.
Kyriacou
,
S.
Voskarides
,
M. S.
Pattichis
,
R.
Istepanian
, and
C. N.
Schizas
,
IEEE Antennas Propag. Mag.
44
(
2
), pp.
143
153
(
2002
).
5.
T.
Chea
, “
Telepresence robots let medical specialists ‘beam’ into remote hospitals | Lubbock Online | Lubbock Avalanche-Journal
,” 2013-11-17,
2013
. [Online]. Available: http://lubbockonline.com/filed-online/2013-11-17/telepresence-robots-let-medical-specialists-beam-remote-hospitals. [Accessed: 24-Jun-2017].
6.
iRobot Corp
., “
FDA Clears First Autonomous Telemedicine Robot for Hospitals | Business Wire
.” [Online]. Available: http://www.businesswire.com/news/home/20130124005134/en/FDA-Clears-Autonomous-Telemedicine-Robot-Hospitals. [Accessed: 24-Jun-2017].
7.
S.
Choudary
, “
Dr Rho - Medical Telepresence Robot :: Create the Future Design Contest
,” 2014-07-2,
2014
. [Online]. Available: https://contest.techbriefs.com/2014/entries/medical/5078. [Accessed: 24-Jun-2017].
8.
R.
LeMoyne
,
T.
Mastroianni
,
A.
Hessel
, and
K.
Nishikawa
, “
Ankle Rehabilitation System with Feedback from a Smartphone Wireless Gyroscope Platform and Machine Learning Classification
,” in
2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA)
, (
IEEE
,
Miami, FL
,
2015
), pp.
406
409
.
9.
S. K.
Islam
,
A.
Fathy
,
Y.
Wang
,
M.
Kuhn
, and
M.
Mahfouz
,
IEEE Microw. Mag.
15
(
7
), pp.
S25
S33
(
2014
).
10.
M.
Sohbati
and
C.
Toumazou
,
IEEE Potentials
34
(
2
), pp.
33
37
(
2015
).
11.
M.
Khalaf
,
A. J.
Hussain
,
D.
Al-Jumeily
,
R.
Keenan
,
P.
Fergus
, and
I. O.
Idowu
, “
Robust Approach for Medical Data Classification and Deploying Self-Care Management System for Sickle Cell Disease
,” in
2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing
, (
IEEE
,
Liverpool, UK, 2015
), pp.
575
580
.
12.
M.
Khalaf
,
A. J.
Hussain
,
D.
Al-Jumeily
,
R.
Keenan
,
R.
Keight
,
P.
Fergus
, and
I. O.
Idowu
, “
Applied Difference Techniques of Machine Learning Algorithm and Web-Based Management System for Sickle Cell Disease
,” in
2015 International Conference on Developments of E-Systems Engineering (DeSE)
, (
IEEE
,
Duai, UAE
,
2015
), pp.
231
235
.
13.
A.
Kazantsev
,
J.
Ponomareva
,
P.
Kazantsev
,
R.
Digilov
, and
Ping
Huang
, “
Development of e-health network for in-home pregnancy surveillance based on artificial intelligence
,” in
Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics
, (
IEEE
,
Hong Kong
,
2012
), pp.
82
84
.
14.
N.
Lasierra
,
A.
Alesanco
, and
J.
Garcia
,
IEEE J. Biomed. Heal. Informatics
18
(
3
), pp.
896
906
(
2014
).
15.
J. M.
Juarez
,
J. M.
Ochotorena
,
M.
Campos
, and
C.
Combi
, “
Multiple Temporal Axes for Visualising the Behaviour of Elders Living Alone
,” in
2013 IEEE International Conference on Healthcare Informatics
, (
IEEE
,
Philadelphia, PA
,
2013
), pp.
387
395
.
16.
Kurnianingsih
,
L. E. Nugroho
,
Widyawan
,
L. Lazuardi
, and
K.
Non-alinsavath
, “
Ontology-based context aware for ubiquitous home care for elderly people
,” in
2015 2nd International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)
, (
IEEE
,
Semarang
,
2015
), pp.
454
459
.
17.
G.
Demiris
,
J. Am. Med. Inform. Assoc.
10
(
4
), pp.
310
4
(
2003
).
18.
A. M.
Bankson
, “
Can artificial intelligence expand health care access? - MIT Sloan School of Management
,” January 20, 2017. [Online]. Available: http://mitsloan.mit.edu/newsroom/articles/can-artificial-intelligence-expand-health-care-access/. [Accessed: 23-Jun-2017].
19.
P.
Matlani
and
N. D.
Londhe
, “A cloud computing based telemedicine service,” in
2013 IEEE Point-of-Care Healthcare Technologies (PHT)
, (
IEEE
,
Bangalore
,
2013
), pp.
326
330
.
20.
A.
Garai
and
A.
Adamko
, “
Comprehensive healthcare interoperability framework integrating telemedicine consumer electronics with cloud architecture
,” in
2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)
, (
IEEE
,
Herl’any
,
2017
), pp.
000411
000416
.
21.
A.-K.
Al-Tamimi
and
A.
Khalifeh
, “
Mobile mules: Modular e-health information synchronization framework
,” in
2014 8th International Symposium on Medical Information and Communication Technology (ISMICT)
, (
IEEE
,
Firenze
,
2014
), pp.
1
5
.
22.
N.
Larburu
,
I.
Widya
,
R. G. A.
Bults
, and
H. J.
Hermens
, “
Making medical treatments resilient to technological disruptions in telemedicine systems
,” in
IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)
, (
IEEE
,
Valencia
,
2014
), pp.
285
288
.
23.
J.
Singh
and
A. K.
Patel
, “An effective telemedicine security using wavelet based watermarking,” in
2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)
, (
IEEE
,
Chennai
,
2016
), pp.
1
6
.
24.
A.
Zhang
,
L.
Wang
,
X.
Ye
, and
X.
Lin
,
IEEE Trans. Inf. Forensics Secur.
12
(
3
), pp.
662
675
(
2017
).
25.
Lemonaid Health - Healthcare. Refreshingly Simple. AZ, CA, CT, FL, GA, Il, MI, NY, OH, OR, PA, RI, VA and WA Only
.” [Online]. Available: https://www.lemonaidhealth.com/#how-it-works. [Accessed: 24-Jun-2017].
26.
C.
Wang
, “
How Telemedicine and Health AI are Transforming Healthcare Experience | Chuhan Wang | Pulse | LinkedIn
,” December 13, 2016. [Online]. Available: https://www.linkedin.com/pulse/how-telemedicine-health-ai-transforming-healthcare-experience-wang. [Accessed: 23-Jun-2017].
27.
A.
Mukhopadhyay
,
S.
Raghunath
, and
M.
Kruti
, “
Feasibility and performance evaluation of VANET techniques to enhance real-time emergency healthcare services
,” in
2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
, (
IEEE
,
Jaipur
,
2016
), pp.
2597
2603
.
28.
Shuai
Zhang
,
S. I.
McClean
,
C. D.
Nugent
,
M. P.
Donnelly
,
L.
Galway
,
B. W.
Scotney
,
I.
Cleland
,
IEEE J. Biomed. Heal. Informatics
18
(
1
), pp.
375
383
(
2014
).
29.
T. K.
Kiong
and
A. S.
Narayanan
, “
A telerehabilitation application with pre-defined consultation classes
,” in
2014 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2014]
, (
2014
, pp.
1238
1244
.
30.
S.
Nubenthan
and
C.
Shalomy
, “
A wireless continuous patient monitoring system for dengue: Wi-Mon
,” in
2017 6th National Conference on Technology and Management (NCTM)
, (
IEEE
,
Nagercoil
,
2017
), pp.
23
27
.
31.
T.
Hofer
,
M.
Schumacher
, and
S.
Bromuri
, “
COMPASS: an Interoperable Personal Health System to Monitor and Compress Signals in Chronic Obstructive Pulmonary Disease
,” in
Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare
, (
IEEE
,
Istanbul
,
2015
), pp
304
311
.
32.
P.
Kumar
,
S. K.
Sharma
, and
S.
Prasad
, “
Detection of fetal electrocardiogram through ofdm, neuro-fuzzy logic and wavelets systems for telemetry
,” in
2016 10th International Conference on Intelligent Systems and Control (ISCO)
, (
IEEE
,
Coimbatore
,
2016
), pp.
1
4
.
33.
F.
Gorunescu
, “
Intelligent decision systems in Medicine ? A short survey on medical diagnosis and patient management
,” in
2015 E-Health and Bioengineering Conference (EHB)
, (
IEEE
,
Iasi
,
2015
), pp.
1
9
.
34.
J.
Lewandowski
,
H. E.
Arochena
,
R. N. G.
Naguib
,
K.-M.
Chao
, and
A.
Garcia-Perez
,
IEEE J. Biomed. Heal. Informatics
18
(
5
), pp.
1525
1532
(
2014
).
35.
A.
Costanzo
,
A.
Faro
,
D.
Giordano
, and
C.
Pino
, “
Mobile cyber physical systems for health care: Functions, ambient ontology and e-diagnostics
,” in
2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)
, (
Las Vegas, NV
,
2016
) pp.
972
975
.
36.
L.
Clifton
,
D. A.
Clifton
,
M. A. F.
Pimentel
,
P. J.
Watkinson
, and
L.
Tarassenko
,
IEEE J. Biomed. Heal. Informatics
,
18
(
3
), pp.
722
730
(
2014
).
37.
A.
Grunerbl
,
A.
Muaremi
,
V.
Osmani
,
G.
Bahle
,
S.
Öhler
,
G.
Tröster
,
O.
Mayora
,
C.
Haring
,
P.
Lukowicz
,
IEEE J. Biomed. Heal. Informatics
19
(
1
), pp.
140
148
(
2015
).
38.
J.
Finkelstein
and
I. C.
Jeong
, “
Using CART for advanced prediction of asthma attacks based on telemonitoring data
,” in
2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
, (
IEEE
,
New York, NY
,
2016
), pp.
1
5
.
39.
C. C. Y.
Poon
,
Yuan-Ting
Zhang
, and
Shu-Di
Bao
,
IEEE Commun. Mag.
44
(
4
), pp.
73
8
(
2006
).
40.
T.
de Jongh
,
I.
Gurol-Urganci
,
V.
Vodopivec-Jamsek
,
J.
Car
, and
R.
Atun
, “Mobile phone messaging telemedicine for facilitating self management of long-term illnesses,” in
Cochrane Database of Systematic Reviews
,
J.
Car
, Ed. Chichester, (
John Wiley & Sons, Ltd
,
UK
,
2008
, UK).
41.
J. S.
Bhatia
and
C.
Singh
, “
Impact of usage of discrete networks on Telemedicine capabilities especially in India
,” in
2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom)
, (
IEEE
,
Greater Noida
,
2014
), pp.
311
318
.
This content is only available via PDF.