Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases

Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety...

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collection Directory of Open Access Books
description Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI.
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spelling doab-20.500.12854ir-987282024-04-09T23:15:54Z Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases Antani, Sameer Rajaraman, Sivaramakrishnan lung conventional radiography diagnostic procedure chronic obstructive pulmonary disease COVID-19 computed tomography lungs variability segmentation hybrid deep learning artificial intelligence deep learning computer-based devices radiology thoracic diagnostic imaging chest X-ray CT observer tests performance lung CT images nodule detection VGG-SegNet pre-trained VGG19 cardiac amyloidosis AL/TTR amyloidosis hypertrophic cardiomyopathy left ventricular hypertrophy convolutional neural network Tuberculosis (TB) drug resistance chest X-rays generalization localization Electrical Impedance Tomography lung imaging cardiopulmonary monitoring aorta lung cancer pulmonary artery pulmonary hypertension modality-specific knowledge object detection RetinaNet ensemble learning pneumonia mean average precision source data set supervised classification coronary artery disease machine learning cardiopulmonary disease faster CNN medical imaging X-rays transfer learning explainability n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI. 2023-04-05T12:48:03Z 2023-04-05T12:48:03Z 2023 book ONIX_20230405_9783036564340_7 9783036564340 9783036564357 https://directory.doabooks.org/handle/20.500.12854/98728 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/6735 https://mdpi.com/books/pdfview/book/6735 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-6435-7 10.3390/books978-3-0365-6435-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036564340 9783036564357 246 Basel open access
spellingShingle lung
conventional radiography
diagnostic procedure
chronic obstructive pulmonary disease
COVID-19
computed tomography
lungs
variability
segmentation
hybrid deep learning
artificial intelligence
deep learning
computer-based devices
radiology
thoracic diagnostic imaging
chest X-ray
CT
observer tests
performance
lung CT images
nodule detection
VGG-SegNet
pre-trained VGG19
cardiac amyloidosis
AL/TTR amyloidosis
hypertrophic cardiomyopathy
left ventricular hypertrophy
convolutional neural network
Tuberculosis (TB)
drug resistance
chest X-rays
generalization
localization
Electrical Impedance Tomography
lung imaging
cardiopulmonary monitoring
aorta
lung cancer
pulmonary artery
pulmonary hypertension
modality-specific knowledge
object detection
RetinaNet
ensemble learning
pneumonia
mean average precision
source data set
supervised classification
coronary artery disease
machine learning
cardiopulmonary disease
faster CNN
medical imaging
X-rays
transfer learning
explainability
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases
title Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases
title_full Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases
title_fullStr Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases
title_full_unstemmed Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases
title_short Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases
title_sort artificial intelligence in image based screening diagnostics and clinical care of cardiopulmonary diseases
topic lung
conventional radiography
diagnostic procedure
chronic obstructive pulmonary disease
COVID-19
computed tomography
lungs
variability
segmentation
hybrid deep learning
artificial intelligence
deep learning
computer-based devices
radiology
thoracic diagnostic imaging
chest X-ray
CT
observer tests
performance
lung CT images
nodule detection
VGG-SegNet
pre-trained VGG19
cardiac amyloidosis
AL/TTR amyloidosis
hypertrophic cardiomyopathy
left ventricular hypertrophy
convolutional neural network
Tuberculosis (TB)
drug resistance
chest X-rays
generalization
localization
Electrical Impedance Tomography
lung imaging
cardiopulmonary monitoring
aorta
lung cancer
pulmonary artery
pulmonary hypertension
modality-specific knowledge
object detection
RetinaNet
ensemble learning
pneumonia
mean average precision
source data set
supervised classification
coronary artery disease
machine learning
cardiopulmonary disease
faster CNN
medical imaging
X-rays
transfer learning
explainability
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
topic_facet lung
conventional radiography
diagnostic procedure
chronic obstructive pulmonary disease
COVID-19
computed tomography
lungs
variability
segmentation
hybrid deep learning
artificial intelligence
deep learning
computer-based devices
radiology
thoracic diagnostic imaging
chest X-ray
CT
observer tests
performance
lung CT images
nodule detection
VGG-SegNet
pre-trained VGG19
cardiac amyloidosis
AL/TTR amyloidosis
hypertrophic cardiomyopathy
left ventricular hypertrophy
convolutional neural network
Tuberculosis (TB)
drug resistance
chest X-rays
generalization
localization
Electrical Impedance Tomography
lung imaging
cardiopulmonary monitoring
aorta
lung cancer
pulmonary artery
pulmonary hypertension
modality-specific knowledge
object detection
RetinaNet
ensemble learning
pneumonia
mean average precision
source data set
supervised classification
coronary artery disease
machine learning
cardiopulmonary disease
faster CNN
medical imaging
X-rays
transfer learning
explainability
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
url ONIX_20230405_9783036564340_7