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• AI will completely change the era of medicine by doctors, mainly in cardiology and radiology. • Pubrica is conducting a meta-analysis in quantitative research about cardiovascular imaging to help future medical researchers and doctors. Full Information: https://bit.ly/2FvQ68c Reference: https://pubrica.com/services/research-services/meta-analysis/ Why Pubrica? When you order our services, we promise you the following – Plagiarism free, always on Time, outstanding customer support, written to Standard, Unlimited Revisions support and High-quality Subject Matter Experts. Contact us : Web: https://pubrica.com/ Blog: https://pubrica.com/academy/ Email: [email protected] WhatsApp : +91 9884350006 United Kingdom: +44-1618186353
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Copyright © 2020 pubrica. All rights reserved 1
An Overview of Meta-Analysis Inthe Field of Cardiovascular Imaging
using Artificial Intelligence
Dr. Nancy Agens, Head,
Technical Operations, Pubrica
In Brief
The most plausible human endeavour
happens in the healthcare sector, has the
greatest impact on artificial intelligence.
Artificial intelligence possesses
superhuman performance in diagnosis,
treatments, clinical testings, etc. AI will
completely change the era of medicine by
doctors, mainly in cardiology and
radiology. Pubrica is conducting a meta-
analysis in quantitative research about
cardiovascular imaging to help future
medical researchers and doctors.
Keywords: Meta-analysis Writing
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Services,
I. INTRODUCTION
As years passing with growing technology,
cardiac diagnostics have potential growth
simultaneously. A huge population starts
accepting imaging techniques for
diagnosis and monitoring treatment in
healthcare sectors that are faster and can
be easily affordable. The interpretation of
imaging is more accurate for satisfying
patients. Writing a meta-analysis about
cardiovascular imaging will be useful for
future studies. Though cardiology has
implanted many numbers of cases using
AI, it is growing recently in the field of
medicine. This blog brings out the
diagnostic tools of cardiology using
artificial intelligence.
II. A META-ANALYSIS OF
CARDIOVASCULAR IMAGING
Echocardiography
Computed tomography
Cardiac MRI
Nuclear imaging
Future aspects
Echocardiography
Echocardiography, as the name, suggests it
will diagnose by ultrasounds. The main
uses of echocardiography are
o Ultrasounds are portable
o More standardized analysis
o The precise interpretation of
data
o Speed
o Can be easily affordable
However, it is a user-dependent tool. AI
has stepped to different echo cardiographic
imaging chain. It has automated
identification of left ventricles by having
algorithms for congenital disorders and
diseases. Some of the other important
diagnosis is phenotypic heart failure and
hypertrophic cardiomyopathy. In general,
it will lead to new hypotheses and perform
a better diagnosis and prognosis in
different cardiac diseases.
Computer Tomography
Computer tomography in cardiovascular
imaging has shown growth over the past
10 years. Some advantages of cardiac CT
are
Copyright © 2020 pubrica. All rights reserved 2
Reduces noise
Better image quality
No need for invasive coronary
angiography for diagnosing
stenosis
The meta-analysis experts say that the
cardiac CT worked by using an artificial
neural network model which determine the
level of calcium from coronary CT
angiography. Another application of
Cardiac CT is to process images. The
visualization of images can be achieved by
the machine learning process. Unlike
echocardiography, Cardiac CT is user-
independent and fast. The major
significance is to reduce radiation
exposure to the patients and helps to create
personalized medicine.
Cardiac MRI
Imaging the heart from various parameters
is done by cardiac Magnetic resonance
imaging.
Functions
Flow imaging
Perfusion imaging
Anatomical imaging
Myocardial characterizations
Contractions
The AI significance can be performed only
by radiographers that have experience in
physics and cardiac anatomy as they are an
integral part of image analysis. However,
the quality of the image is both user and
vendor dependent.
The main objectives of cardiac MRI
Automated segmentation of heart
structure
Infarct tissue analysis.
The studies carried out by Cardiac MRI
are
Component analysis in pulmonary
hypertension for patients
Worsening of left ventricular
function for patients with
a repaired tetralogy of Fallot
Due to these major disadvantages, MRI
has become more challenging in imaging
than others. Researchers are performing
with various ideas to overcome those
challenges.
Nuclear imaging
Nuclear imaging in cardiology is used to
determine the faults in the myocardium
wall.
Methods
Myocardial perfusion single-
photon emission computed
tomography (spect)
Positron emission tomography(pet)
1. SPECT
SPECT detects the gamma rays emitted by
the radioactive tracer to reconstruct the
tissue. SPECT is used to diagnose the
abnormal myocardium and it is interpreted
using Artificial neural network models.
The accuracy of data was boosted by
machine learning.
It also detects
Stress
Stress-induced ischaemia
Rest defects
2. PET
PET detects the two concurrent opposite
annihilation photos. Both spect and PET
are similar to CT and MRI.
Disadvantages
It leads to radiation exposure in humans
III. FUTURE ASPECTS
There will be a huge opportunity for AI
implementation in future research from
machine learning sources.
Biomarkers
Genomics
Proteomics
Metabolomics
This can improve the healthcare standard
and quality in the treatment of patients.
The future researchers can work on the
challenges of the imaging techniques using
meta-analysis writing services
VI. CONCLUSION
The cardiovascular imaging has shown
remarkable growth over the past few years.
It not only gives structural data but also
Copyright © 2020 pubrica. All rights reserved 2
physiological and molecular features of the
heart. AI set up a huge platform to
healthcare from past to present and even in
future. Pubrica established a meta analysis
of artificial intelligence in cardiovascular
imaging.
REFERENCES
1. Siegersma, K. R., Leiner, T., Chew, D. P.,
Appelman, Y., Hofstra, L., &Verjans, J. W. (2019).
Artificial intelligence in cardiovascular imaging:
state of the art and implications for the imaging
cardiologist. Netherlands Heart Journal, 1-11.
2. Krittanawong, C., Zhang, H., Wang, Z., Aydar, M.,
&Kitai, T. (2017). Artificial intelligence in
precision cardiovascular medicine. Journal of the
American College of Cardiology, 69(21), 2657-
2664.
3. Dey, D., Slomka, P. J., Leeson, P., Comaniciu, D.,
Shrestha, S., Sengupta, P. P., & Marwick, T. H.
(2019). Artificial intelligence in cardiovascular
imaging: JACC state-of-the-art review. Journal of
the American College of Cardiology, 73(11), 1317-
1335.
4. Johnson, K. W., Soto, J. T., Glicksberg, B. S.,
Shameer, K., Miotto, R., Ali, M., ...& Dudley, J. T.
(2018). Artificial intelligence in cardiology. Journal
of the American College of Cardiology, 71(23),
2668-2679.