RIT computing students and Professor Rui Li are working on a National Institutes of Health-funded project to use AI in ...

Causal AI transforms key areas of manufacturing by revealing what happens and why. In predictive maintenance, it shifts focus from forecasting failures to understanding how maintenance strategies ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

This important study used five metrics to compare the cost-effectiveness of intramural and extramural research funded by the National Institutes of Health in the United States between 2009 and 2019.

Objective Organ damage is a key determinant of poor prognosis and increased mortality in systemic lupus erythematosus (SLE).

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to cleaning ingredients (handling missing values, standardization) Model ...

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...

Background: This study aimed to evaluate the predictive utility of routine hematological, inflammatory, and metabolic markers for bacteremia and to compare the classification performance of logistic ...

Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...

Background: Perioperative venous thromboembolism (VTE) is a severe complication in lung cancer surgery. Traditional prediction models have limitations in handling complex clinical data, whereas ...