Machine Learning in Point of Care Ultrasound

Sonko, Momodou L.; Arnold, Thomas C.; Кузнецов, И. А.

doi:10.24908/pocus.v7ikidney.15345

Cited by 11 publications

(5 citation statements)

References 48 publications

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“…Point-of-Care Ultrasound (POCUS), which has been used for the diagnosis and treatment of various diseases since the 1990s, has also rapidly increased its use with the introduction of portable device, and is useful for primary care of patients along with stethoscopes [ 62 ]. Like a stethoscope, POCUS is non-invasive and can be performed right on the bed without moving the patient to the examination room.…”

Section: Discussionmentioning

confidence: 99%

“…Point-of-Care Ultrasound (POCUS), which has been used for the diagnosis and treatment of various diseases since the 1990s, has also rapidly increased its use with the introduction of portable device, and is useful for primary care of patients along with stethoscopes 62 . Like a stethoscope, POCUS is non-invasive and can In conclusion, the stethoscope is expected to develop through steady research in the future, and to be used as more popular medical devices through the application of AI analysis programs and development of wearable device.…”

Section: Discussionmentioning

confidence: 99%

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Evolution of the Stethoscope: Advances with the Adoption of Machine Learning and Development of Wearable Devices

Kim,

Hyon,

Woo

et al. 2023

Tuberc Respir Dis

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The stethoscope has long been used for the examination of patients, but the importance of auscultation has declined due to its several limitations and the development of other diagnostic tools. However, auscultation is still recognized as a primary diagnostic device because it is non-invasive and provides valuable information in real-time. To supplement the limitations of existing stethoscopes, digital stethoscopes with machine learning (ML) algorithms have been developed. Thus, now we can record and share respiratory sounds and artificial intelligence (AI)-assisted auscultation using ML algorithms distinguishes the type of sounds. Recently, the demands for remote care and non-face-to-face treatment diseases requiring isolation such as coronavirus disease 2019 (COVID-19) infection increased. To address these problems, wireless and wearable stethoscopes are being developed with the advances in battery technology and integrated sensors. This review provides the history of the stethoscope and classification of respiratory sounds, describes ML algorithms, and introduces new auscultation methods based on AI-assisted analysis and wireless or wearable stethoscopes.

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Section: Discussionmentioning

confidence: 99%

“…Point-of-Care Ultrasound (POCUS), which has been used for the diagnosis and treatment of various diseases since the 1990s, has also rapidly increased its use with the introduction of portable device, and is useful for primary care of patients along with stethoscopes 62 . Like a stethoscope, POCUS is non-invasive and can In conclusion, the stethoscope is expected to develop through steady research in the future, and to be used as more popular medical devices through the application of AI analysis programs and development of wearable device.…”

Section: Discussionmentioning

confidence: 99%

Evolution of the Stethoscope: Advances with the Adoption of Machine Learning and Development of Wearable Devices

Kim,

Hyon,

Woo

et al. 2023

Tuberc Respir Dis

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show abstract

“…Although not all AI-based solutions were appropriately validated, e.g. by the FDA, they have already been widely implemented in clinical conditions [ 25 ]. A recent document issued by the FDA regarding the use of AI in medical devices states the following: “Artificial intelligence-based technologies have the potential to transform healthcare by deriving new and important insights from the vast amount of data generated during the delivery of healthcare every day”.…”

Section: The Use Of Ai In Clinical Ultrasonographymentioning

confidence: 99%

Overview of artificial intelligence in point-of-care ultrasound. New horizons for respiratory system diagnoses

Mika,

Gola,

Gil-Mika

et al. 2024

ait

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Throughout the past decades ultrasonography did not prove to be a procedure of choice if regarded as part of the routine bedside examination. The reason was the assumption defining the lungs and the bone structures as impenetrable by ultrasound. Only during the recent several years has the approach to the use of such tool in clinical daily routines changed dramatically to offer so-called point-of-care ultrasonography (POCUS). Both vertical and horizontal artefacts became valuable sources of information about the patient’s clinical condition, assisting therefore the medical practitioner in differential diagnosis and monitoring of the patient. What is important is that the information is delivered in real time, and the procedure itself is non-invasive. The next stage marking the progress made in this area of diagnostic imaging is the development of arti-ficial intelligence (AI) based on machine learning algorithms. This article is intended to present the available, innovative solutions of the ultrasound systems, including Smart B-line technology, to ensure automatic identification process, as well as interpretation of B-lines in the given lung area of the examined patient. The article sums up the state of the art in ultrasound artefacts and AI applied in POCUS.

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“…The previously mentioned B-line score technique for assessing pulmonary congestion using POCUS has not achieved widespread usage, partly because the assessment is tedious. Addressing this, DL models using convolutional neural networks have been developed to automatically quantify B-line scores from POCUS lung videos ( 110 ).…”

Section: Open Challenges and The Future Of Ultrasoundmentioning

confidence: 99%

Critical Advances for Democratizing Ultrasound Diagnostics in Human and Veterinary Medicine

Kaffas,

Vo-Phamhi,

Griffin

et al. 2024

Annual Review of Biomedical Engineering

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The democratization of ultrasound imaging refers to the process of making ultrasound technology more accessible. Traditionally, ultrasound imaging has been predominately used in specialized medical facilities by trained professionals. Advancements in technology and changes in the health-care landscape have inspired efforts to broaden the availability of ultrasound imaging to various settings such as remote and resource-limited areas. In this review, we highlight several key factors that have contributed to the ongoing democratization of ultrasound imaging, including portable and handheld devices, recent advancements in technology, and training and education. Examples of diagnostic point-of-care ultrasound (POCUS) imaging used in emergency and critical care, gastroenterology, musculoskeletal applications, and other practices are provided for both human and veterinary medicine. Open challenges and the future of POCUS imaging are presented, including the emerging role of artificial intelligence in technology development. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 26 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Machine Learning in Point of Care Ultrasound

Cited by 11 publications

References 48 publications

Evolution of the Stethoscope: Advances with the Adoption of Machine Learning and Development of Wearable Devices

Evolution of the Stethoscope: Advances with the Adoption of Machine Learning and Development of Wearable Devices

Overview of artificial intelligence in point-of-care ultrasound. New horizons for respiratory system diagnoses

Critical Advances for Democratizing Ultrasound Diagnostics in Human and Veterinary Medicine

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