Artificial intelligence of things for smarter healthcare: A survey of advancements, challenges, and opportunities
Healthcare systems are under increasing strain due to a myriad of factors, from a steadily
ageing global population to the current COVID-19 pandemic. In a world where we have …
ageing global population to the current COVID-19 pandemic. In a world where we have …
Machine learning techniques for diagnosis of alzheimer disease, mild cognitive disorder, and other types of dementia
Alzheimer's disease (AD) is one of the most common form of dementia which mostly affects
elderly people. AD identification in early stages is a difficult task in medical practice and …
elderly people. AD identification in early stages is a difficult task in medical practice and …
Genetics and sports performance: the present and future in the identification of talent for sports based on DNA testing
D Varillas-Delgado, J Del Coso… - European journal of …, 2022 - Springer
The impact of genetics on physiology and sports performance is one of the most debated
research aspects in sports sciences. Nearly 200 genetic polymorphisms have been found to …
research aspects in sports sciences. Nearly 200 genetic polymorphisms have been found to …
Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence
AK Bonkhoff, C Grefkes - Brain, 2022 - academic.oup.com
Stroke ranks among the leading causes for morbidity and mortality worldwide. New and
continuously improving treatment options such as thrombolysis and thrombectomy have …
continuously improving treatment options such as thrombolysis and thrombectomy have …
Machine learning in action: stroke diagnosis and outcome prediction
The application of machine learning has rapidly evolved in medicine over the past decade.
In stroke, commercially available machine learning algorithms have already been …
In stroke, commercially available machine learning algorithms have already been …
A systematic review of machine learning models for predicting outcomes of stroke with structured data
Background and purpose Machine learning (ML) has attracted much attention with the hope
that it could make use of large, routinely collected datasets and deliver accurate …
that it could make use of large, routinely collected datasets and deliver accurate …
[HTML][HTML] Machine learning predictive models for acute pancreatitis: a systematic review
Y Zhou, Y Ge, X Shi, K Wu, W Chen, Y Ding… - International journal of …, 2022 - Elsevier
Introduction Acute pancreatitis (AP) is a common clinical pancreatic disease. Patients with
different severity levels have different clinical outcomes. With the advantages of algorithms …
different severity levels have different clinical outcomes. With the advantages of algorithms …
Machine learning and acute stroke imaging
SA Sheth, L Giancardo, M Colasurdo… - Journal of …, 2023 - jnis.bmj.com
Background In recent years, machine learning (ML) has had notable success in providing
automated analyses of neuroimaging studies, and its role is likely to increase in the future …
automated analyses of neuroimaging studies, and its role is likely to increase in the future …
The current research landscape of the application of artificial intelligence in managing cerebrovascular and heart diseases: A bibliometric and content analysis
The applications of artificial intelligence (AI) in aiding clinical decision-making and
management of stroke and heart diseases have become increasingly common in recent …
management of stroke and heart diseases have become increasingly common in recent …
Machine learning applications in stroke medicine: Advancements, challenges, and future prospectives
M Daidone, S Ferrantelli… - Neural Regeneration …, 2024 - journals.lww.com
Stroke is a leading cause of disability and mortality worldwide, necessitating the
development of advanced technologies to improve its diagnosis, treatment, and patient …
development of advanced technologies to improve its diagnosis, treatment, and patient …