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Meta-analysis in the field of cardiovascular imaging using artificial intelligence - Pubrica
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.
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.
A meta-analysis of cardiovascular
imaging:
Ø Echocardiography
Ø Computed tomography
Ø Cardiac MRI
Ø Nuclear imaging
Ø 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
Computer Tomography:
Computer
tomography in cardiovascular imaging has shown
growth over the past 10 years. Some advantages of cardiac CT are
Ø Reduces
noise
Ø Better
image quality
Ø 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.
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.
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
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
Conclusion
The cardiovascular imaging has shown
remarkable growth over the past few years. It not only gives structural data
but also physiological and molecular features of the heart.
Full Information: https://bit.ly/2FvQ68c
Reference: https://pubrica.com/services/research-services/meta-analysis/
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on Time, outstanding customer support, written to Standard, Unlimited Revisions
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