[HTML][HTML] Artificial intelligence, nano-technology and genomic medicine: the future of anaesthesia

S Naaz, A Asghar - Journal of Anaesthesiology Clinical …, 2022 - journals.lww.com
Nanotechnology with artificial intelligence (AI) can metamorphose medicine to an extent that
has never been achieved before. AI could be used in anesthesia to develop advanced …

Factors influencing the acceptance of healthcare information technologies: A meta-analysis

AYL Chong, M Blut, S Zheng - Information & Management, 2022 - Elsevier
Healthcare information technologies (HIT) can address several challenges faced by
healthcare systems. To benefit from the advantages HIT offer, users must first accept them …

[HTML][HTML] Factors determining membership in community-based health insurance in West Africa: a scoping review

KK Conde, AM Camara, M Jallal, M Khalis… - Global Health Research …, 2022 - Springer
Background In many low-income countries, households bear most of the health care costs.
Community-based health insurance (CBHI) schemes have multiplied since the 1990s in …

[HTML][HTML] Global trends in incidence and death of neonatal disorders and its specific causes in 204 countries/territories during 1990–2019

Z Ou, D Yu, Y Liang, H He, W He, Y Li, M Zhang… - BMC public health, 2022 - Springer
Background Neonatal disorders (ND) are a significant global health issue. This article aimed
to track the global trends of neonatal disorders in 204 countries/territories from 1990 to 2019 …

[HTML][HTML] Global, regional, and national years lived with disability due to blindness and vision loss from 1990 to 2019: Findings from the Global Burden of Disease Study …

S Li, E Ye, J Huang, J Wang, Y Zhao, D Niu… - Frontiers in Public …, 2022 - frontiersin.org
Purpose This study aimed to provide a comprehensive assessment of burden estimates and
the secular trend of blindness and vision loss, as measured by years lived with disability …

[HTML][HTML] The projection of Iran's healthcare expenditures by 2030: evidence of a time-series analysis

N Jahanmehr, M Noferesti, S Damiri… - … journal of health …, 2022 - ncbi.nlm.nih.gov
Background: The projection of levels and composition of financial resources for the
healthcare expenditure (HCE) and relevant trends can provide a basis for future health …

Process mining in healthcare: Challenges and promising directions

R Gatta, S Orini, M Vallati - Artificial Intelligence in Healthcare: Recent …, 2022 - Springer
Process mining for healthcare is the discipline that focuses on mining, analysing, and
enhancing real-world healthcare processes. In this chapter, we provide a compelling …

[HTML][HTML] A mixed methods study of community-based health insurance enrollment trends and underlying challenges in two districts of northeast Ethiopia: A proxy for its …

M Hussien, M Azage, NB Bayou - Plos one, 2022 - journals.plos.org
Background The term" community-based health insurance" refers to a broad range of
nonprofit, prepaid health financing models designed to meet the health financing needs of …

[PDF][PDF] A taxonomy of machine learning-based fraud detection systems

T Matschak, S Trang, C Prinz - 2022 - researchgate.net
As fundamental changes in information systems drive digitalization, the heavy reliance on
computers today significantly increases the risk of fraud. Existing literature promotes …

Show Me Your Claims and I'll Tell You Your Offenses: Machine Learning-Based Decision Support for Fraud Detection on Medical Claim Data

T Matschak, C Prinz, F Rampold, S Trang - 2022 - aisel.aisnet.org
Health insurance claim fraud is a serious issue for the healthcare industry as it drives up
costs and inefficiency. Therefore, claim fraud must be effectively detected to provide …