Assembly Mag6d
Some Experiences Integrating Machine Learning with Vision and Robotics
Is ML Useful In Integration? You may (still) be wondering whether any of this stuff is actually useful in real-world ...
A step-by-step tutorial for applying machine learning to drug resistance
Antimicrobial resistance is a growing health crisis that could lead to millions of deaths by 2050, according to the World ...
Visual Studio Magazine1d
Naive Bayes Regression Using C#
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the naive Bayes regression technique, where the goal is to predict a single numeric value. Compared to other ...
northpennnow8h
Franklin Burgess: How to Get Started with Machine Learning Programming
Machine learning programming is an evolving field that enables computers to learn from data and make predictions or decisions without explicit programming. It is a subset of artificial intelligence ...
Scientific Research Publishing3d
Evaluations of Machine Learning Algorithms Using Simulation Study ()
Khatun, N. (2025) Evaluations of Machine Learning Algorithms Using Simulation Study. Open Journal of Statistics, 15, 41-52.
Too Old to Operate8d
In Lung Cancer, Novel Preoperative Biomarkers Predict Recurrence Risk
Using preoperative chest CT scans, researchers identified novel preoperative biomarkers for lung cancer recurrence ...
Endocrinology Advisor20h
Performance of AI Preeclampsia Prediction Models Deteriorates Over Time
Machine Learning (PIERS-ML) model and the logistic regression-based fullPIERS model, consecutive performance deteriorates over time.
Too Old to Operate11d
Development of machine learning prognostic models for overall survival of epithelial ovarian cancer patients: a seer-based study.
To develop a machine learning (ML) algorithm to predict survival probabilities for patients with epithelial ovarian cancer (EOC).Data were obtained from the SEER database for women diagnosed with EOC ...