The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CKD). COVID-19 patients with CKD will face a ...
This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and use machine learning (ML) methods to establish an effective algorithm for predicting co-infection ...
Introduction Sepsis is a life-threatening condition in intensive care units (ICUs), where any delay in diagnosis and treatment can lead to organ dysfunction, prolonged hospital stay and increased ...
shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area We trained and validated two-phase ML ...
Hospitals’ AI adoption has exploded during the past decade, with predictive analytics being one of the most prevalent use cases. Predictive algorithms have become widely used due to their ability to ...
AI/ML technologies are revolutionizing pharmaceutical formulation by optimizing excipient selection and predicting stability, reducing time and resources needed for development. Poor solubility of ...
Quantum computers, systems that process information leveraging quantum mechanical effects, have the potential of ...
Technology startup MainRail has announced the development of predictive algorithms for the risk of rail buckling in ballasted tracks. By coordinating with the construction firm Azvi, MainRail started ...
While programs such as Artificial Intelligence bots that can write poetry or develop art are capturing people’s interest, administrative agencies across the country are concerned about how similar ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results