Zobrazeno 1 - 10
of 570
pro vyhledávání: '"healthcare analytics"'
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-20 (2024)
Abstract This study reviews the studies utilizing Artificial Intelligence (AI) and AI-driven tools and methods in managing Acute Kidney Injury (AKI). It categorizes the studies according to medical specialties, analyses the gaps in the existing resea
Externí odkaz:
https://doaj.org/article/03e4036ab9bc49d28a4ad6a0c466b15f
Autor:
Haitham Jahrami, Amir H. Pakpour, Waqar Husain, Achraf Ammar, Zahra Saif, Ali Husain Alsalman, Adel Aloffi, Khaled Trabelsi, Seithikurippu R. Pandi-Perumal, Michael V. Vitiello
Publikováno v:
BMC Psychiatry, Vol 24, Iss 1, Pp 1-9 (2024)
Abstract Background Hoarding disorder (HD) is characterized by a compulsion to collect belongings, and to experience significant distress when parting from them. HD is often misdiagnosed for several reasons. These include patient and family lack of r
Externí odkaz:
https://doaj.org/article/7add043437194b0c8cd83a6ed6255ca2
Autor:
Pritam Chakraborty, Anjan Bandyopadhyay, Preeti Padma Sahu, Aniket Burman, Saurav Mallik, Najah Alsubaie, Mohamed Abbas, Mohammed S. Alqahtani, Ben Othman Soufiene
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-23 (2024)
Abstract Stroke prediction remains a critical area of research in healthcare, aiming to enhance early intervention and patient care strategies. This study investigates the efficacy of machine learning techniques, particularly principal component anal
Externí odkaz:
https://doaj.org/article/ad13fbd4562842c1ad6f140bd7a145c9
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-29 (2024)
Abstract Background Governments worldwide are facing growing pressure to increase transparency, as citizens demand greater insight into decision-making processes and public spending. An example is the release of open healthcare data to researchers, a
Externí odkaz:
https://doaj.org/article/96c9d98388084bd9b992e686cb0f2905
Autor:
Abeer Aljohani
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-23 (2024)
Abstract Advanced data analytics are increasingly being employed in healthcare research to improve patient classification and personalize medicinal therapies. In this paper, we focus on the critical problem of clustering electronic health record (EHR
Externí odkaz:
https://doaj.org/article/74b26c93e1134969bde7c3edabe93756
Publikováno v:
IEEE Access, Vol 12, Pp 171205-171220 (2024)
Chronic Kidney Disease (CKD) remains a significant global health challenge, with increasing prevalence and a substantial impact on patient quality of life. Early and accurate prediction of CKD risk is crucial for timely intervention and management. T
Externí odkaz:
https://doaj.org/article/1add961bcd754646b1188611b7bcd959
Publikováno v:
IEEE Access, Vol 12, Pp 166058-166067 (2024)
Healthcare systems face significant challenges and financial burdens due to patient no-shows, highlighting the need for accurate and interpretable predictive models. This study evaluated the efficacy of twelve classification algorithms that can gener
Externí odkaz:
https://doaj.org/article/dc5a5434576b41cab859b0f2aed9ffc4
Autor:
Haseeb Javed, Hafiz Abdul Muqeet, Amirhossein Danesh, Atiq Ur Rehman, Tahir Javed, Amine Bermak
Publikováno v:
IEEE Access, Vol 12, Pp 141064-141087 (2024)
This review paper examines the transformative role of artificial intelligence (AI) and dynamic ensemble techniques in enhancing healthcare services. By systematically reviewing literature and case studies from the past decade, we explore how these ad
Externí odkaz:
https://doaj.org/article/7ec49cd80ee74b56a1061df9fe4e9d28
Publikováno v:
IEEE Access, Vol 12, Pp 10254-10280 (2024)
This research is imperative due to the pressing need for improved patient recruitment in clinical trials, addressing challenges such as delays and high costs. By introducing a classification model and a game theoretic approach for clinical trial sett
Externí odkaz:
https://doaj.org/article/a1a0601209334e0b827a85b8b7f01b8f
Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI
Autor:
Insu Jeon, Minjoong Kim, Dayeong So, Eun Young Kim, Yunyoung Nam, Seungsoo Kim, Sehoon Shim, Joungmin Kim, Jihoon Moon
Publikováno v:
Diagnostics, Vol 14, Iss 22, p 2504 (2024)
Background: As the demand for early and accurate diagnosis of autism spectrum disorder (ASD) increases, the integration of machine learning (ML) and explainable artificial intelligence (XAI) is emerging as a critical advancement that promises to revo
Externí odkaz:
https://doaj.org/article/3e6cd5582ab2499b951b639b6750d3cf