Government Technology

Using Machine Learning to Understand College Closures

Researchers worked with the Federal Reserve to create a predictive model that assesses hundreds of institutional ...

Carziqo Advances Scalable Autonomous Driving Through Real-World Data Learning Architecture

Carziqo is a smart mobility technology company focused on developing scalable autonomous driving solutions through real-world ...
EurekAlert!

Multimodal learning-based prediction for nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
SDxCentral

AI inferencing will define 2026, and the market's wide open

AWS, Cisco, CoreWeave, Nutanix and more make the inference case as hyperscalers, neoclouds, open clouds, and storage go ...
BMJ Open

Development and evaluation of a diagnostic aiding tool for differentiating tropical fevers using artificial intelligence approach: a study protocol from tertiary care hospital ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
IEEE

Fitting Multiple Machine Learning Models With Performance Based Clustering

Abstract: Traditional machine learning approaches assume that data comes from a single generating mechanism, which may not hold for most real life data. In these cases, the single mechanism assumption ...
IEEE

Enhancing Cloud Security: A Multi-Factor Authentication and Adaptive Cryptography Approach Using Machine Learning Techniques

Abstract: The rapid expansion of cloud computing underscores the critical need for advanced security measures to protect sensitive data on remote servers. Authentication is crucial for safeguarding ...
Frontiers

Interpretable machine learning model for identification and risk factor of premature rupture of membranes (PROM) and its association with nutritional inflammatory index: a ...

Department of Obstetrics and Gynecology, Binhai County People’s Hospital, Yancheng, Jiangsu, China Background: Premature rupture of membranes (PROM) poses significant risks to both maternal and ...
Frontiers

A machine learning model for robust prediction of sepsis-induced coagulopathy in critically ill patients with sepsis

Introduction: Sepsis-induced coagulopathy (SIC) is a common disease in patients with sepsis. It denotes higher mortality rates and a poorer prognosis in these patients. This study aimed to develop a ...