Download Gekko Optimization to build, simulate, and solve advanced engineering and data models in one open source package. Explore practical workflows for equations, prediction, control, and Gekko ...

Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...

Researchers have shown that blending quantum computing with AI can dramatically improve predictions of complex, chaotic systems. By letting a quantum computer identify hidden patterns in data, the AI ...

Abstract: Being able to leverage data held across multiple systems for predictive modeling is essential to comprehensively study outcomes of interest, as it allows the integration of multiple ...

Thoracoscopic wedge resection has become a standard procedure for pulmonary nodule management, yet postoperative air leak (PAL) remains a prevalent complication. While bovine pericardial patches are ...

World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, training these models directly from pixel data often leads to ‘representation ...

Predictive modeling firm Recentive Analytics raised a $45M Series B funding round led by Wavecrest Growth Partners, with participation from Arthur Blank through AMB Sports and Entertainment and Steve ...

ABSTRACT: Accurate suicide risk prediction in clinical practice is hindered by stringent privacy regulations, fragmented data ownership, and pronounced heterogeneity across healthcare institutions in ...

Ph.D. Economist & Data Scientist. Specialist in econometrics & ETL. Transforming complex data into policy. Higher education institutions have historically relied on retrospective reporting to ...

ABSTRACT: Amyloid-β (Aβ) pathology can be detected years before clinical Alzheimer’s disease (AD), yet forecasting who will decline—and how rapidly—remains difficult in cognitively unimpaired (CU) and ...