Title
Unapređenje koncepta medicinskih informacionih sistema u cilju smanjenja efekata i posledica epidemija i pandemija
Creator
MIlenković, Aleksandar M., 1985-
CONOR:
34174311
Copyright date
2021
Object Links
Select license
Autorstvo-Nekomercijalno-Bez prerade 3.0 Srbija (CC BY-NC-ND 3.0)
License description
Dozvoljavate samo preuzimanje i distribuciju dela, ako/dok se pravilno naznačava ime autora, bez ikakvih promena dela i bez prava komercijalnog korišćenja dela. Ova licenca je najstroža CC licenca. Osnovni opis Licence: http://creativecommons.org/licenses/by-nc-nd/3.0/rs/deed.sr_LATN. Sadržaj ugovora u celini: http://creativecommons.org/licenses/by-nc-nd/3.0/rs/legalcode.sr-Latn
Language
Serbian
Cobiss-ID
Theses Type
Doktorska disertacija
description
Datum odbrane: 19.04.2022.
Other responsibilities
Academic Expertise
Društveno-humanističke nauke
University
Univerzitet u Nišu
Faculty
Fakultet sporta i fizičkog vaspitanja
Group
Katedra za teorijsko-metodološke predmete
Alternative title
Improving the concept of medical information systems in order to reduce the effects and consequences of epidemics and pandemics
Publisher
[A. M. Milenković]
Format
221 str.
description
Biografija autora: str. 217,
Bibliografija: str. 194-205.
description
Medical Informatics
Abstract (en)
The emergence and fast expansion of huge epidemics and
pandemics besides the effect on everyday life of people through the
change of health, economic, social and political routine, greatly
influence the existing IT products, with a significant emphasis on large
information systems which are exploited daily.
The main issue which naturally arises is the effective decrease
of the rapid spread of epidemics. The reduction of disease transmission
is most effectively achieved by socially distancing people and reducing
their contacts.
In addition to engaging health resources in combating the
epidemic, there is also a need for the intensive use of IT solutions that
can help slowdown the spread of epidemics, enable continuous
monitoring of the affected area, enable rapid and early diagnosis of
diseases, reduce contacts between infected and uninfected people,
predict trends of the spread of epidemics in order to act in a targeted
and proactive manner, etc.
This doctoral dissertation presents an improved concept of
medical information systems which is aimed at the reduction of effects
and consequences of epidemics and pandemics. It enables a better
response of the medical information system to the challenges which
will be posed by future epidemics and pandemics, not just the COVID-
19 pandemic, which was taken as a case study. The concepts proposed
in this doctoral dissertation are applicable to all existing medical
information systems both in the Republic of Serbia and in the region.
The main objective of the scientific research is to improve the
concept of medical information systems in order to reduce the effects
and consequences of epidemics and pandemics.
The most important objectives of this doctoral dissertation are:
the improved concept of medical information system, improved level
of collaboration of medical information systems with other information
systems outside of the primary health care level, increased level of
social distance by implementing new medical information system
services, proposed machine learning model for the fast and early
diagnosis of COVID -19 disease based on radiological images of lungs,
timely and accurate reporting in order to provide conditions for the
rapid and adequate response and planning of human and material
resources allocation, confirmation of proposed concepts by the
practical implementation of certain proposed services and
functionalities built into the real medical information system
MEDIS.NET which is used daily.
Authors Key words
medicinski informacioni sistem, pandemija, socijalni kontakti, korona
virus, COVID-19, servisi e-zdravstva, duboko učenje, duboke
neuronske mreže, kontrolna tabla, personalizovani automati za
izdavanje lekova
Authors Key words
medical information system, pandemic, social contacts, coronavirus,
COVID-19, e-Health services, deep learning, deep neural network,
live dashboard, personalized medicine vending machines
Classification
004.7/.8:[616.98:578.834(043.3)
614.4:004.8.032.26(043.3)
Subject
T120
Type
Tekst
Abstract (en)
The emergence and fast expansion of huge epidemics and
pandemics besides the effect on everyday life of people through the
change of health, economic, social and political routine, greatly
influence the existing IT products, with a significant emphasis on large
information systems which are exploited daily.
The main issue which naturally arises is the effective decrease
of the rapid spread of epidemics. The reduction of disease transmission
is most effectively achieved by socially distancing people and reducing
their contacts.
In addition to engaging health resources in combating the
epidemic, there is also a need for the intensive use of IT solutions that
can help slowdown the spread of epidemics, enable continuous
monitoring of the affected area, enable rapid and early diagnosis of
diseases, reduce contacts between infected and uninfected people,
predict trends of the spread of epidemics in order to act in a targeted
and proactive manner, etc.
This doctoral dissertation presents an improved concept of
medical information systems which is aimed at the reduction of effects
and consequences of epidemics and pandemics. It enables a better
response of the medical information system to the challenges which
will be posed by future epidemics and pandemics, not just the COVID-
19 pandemic, which was taken as a case study. The concepts proposed
in this doctoral dissertation are applicable to all existing medical
information systems both in the Republic of Serbia and in the region.
The main objective of the scientific research is to improve the
concept of medical information systems in order to reduce the effects
and consequences of epidemics and pandemics.
The most important objectives of this doctoral dissertation are:
the improved concept of medical information system, improved level
of collaboration of medical information systems with other information
systems outside of the primary health care level, increased level of
social distance by implementing new medical information system
services, proposed machine learning model for the fast and early
diagnosis of COVID -19 disease based on radiological images of lungs,
timely and accurate reporting in order to provide conditions for the
rapid and adequate response and planning of human and material
resources allocation, confirmation of proposed concepts by the
practical implementation of certain proposed services and
functionalities built into the real medical information system
MEDIS.NET which is used daily.
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