BIOENGINEER

Machine-learning model shows moderate accuracy for predicting specialist nurse transfer intentions

A model-development study using 471 specialist nurse samples achieved an AUC of 0.766 for distinguishing stated transfer ...

[Part 3] Predicting Numbers or Choosing Categories?: A Gentle Explanation of Regression and Classification

Estimated reading time: approx. 3 minutes 30 secondsIn machine learning, models learned from past data are used to predict ...
BIOENGINEER

Ridge regression outperforms nonlinear models for petrol price prediction in regulated Zambia

A machine-learning study using 2011–2025 data from Zambia’s regulated fuel-pricing system found that Ridge regression ...
ascopubs.org

Machine Learning Model for Predicting Severe Adverse Events in Oncology Patients Using the US Food and Drug Administration Adverse Event Reporting System

Cost-Effectiveness of Maintaining Higher Stem-Cell Collection Thresholds in the Chimeric Antigen Receptor T-Cell Era for Multiple Myeloma Predicting severe adverse events (SAEs) in oncology is ...
Analytics Insight

Predictive AI and the Challenge of Forecasting Market Volatility

Predictive AI uses advanced deep learning architectures to analyze structured and unstructured datasets to forecast financial ...

Production-Level Machine Learning in FinTech: Designing Data Integrity, Model Validation, and Reliable Decision-Making Systems

Machine learning in financial services operates under different constraints than general-purpose prediction systems.In areas ...
The Conversation

Machines whisper before they scream: we built an AI model that predicts expensive problems

In most industries, maintenance is a waiting game. Things are fixed when they break. But in the 21st century, an age defined by data and automation, that approach no longer makes sense. The solution ...
Rebellion Research

Machine Learning for Venture Capital: From Data Signals to Investment Decisions

Discover how machine learning for venture capital enhances deal sourcing and diligence. Turn fragmented startup data into ...