A urine-based biological aging clock: Machine learning and microRNA offer accurate prediction

Craif Inc. in Nagoya, Japan, working with Nagoya University's Institute of Innovation for Future Society, has developed a ...
European Medical Journal

Machine Learning Shows Promise in Predicting RA Treatment Response

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
Oncology Nurse Advisor

Machine Learning Model Predicts Nutritional Risk in Nasopharyngeal Carcinoma

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
Analytics Insight

Data Science: Building Machine Learning Models, Harvard University

Harvard University presents its eight-week online course through edX, which imparts to students essential knowledge of ...
Medical Dialogues

Machine Learning Reliably Predicts Early Dysphagia After Stroke, suggests study

According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...
GEN

Machine Learning an Ideal Fit for Process Validation

Validating drug production processes need not be a headache, according to AI researchers, who say machine learning could be a single answer to biopharma’s multivariate problem. The FDA defines process ...
Machine Design

Standardizing Computational Models: Verification, Validation and Uncertainty Quantification

Computational models and simulations have had an important role in engineering analysis since as far back as the 1960s. It is widely recognized that the use of modeling and simulation tools can make ...

Enhancing machine-learning interatomic potentials for advanced materials modeling

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...
Analytics Insight

10 Most Common Machine Learning Mistakes and Tips to Fix Them

Overview: Machine learning failures usually start before modeling, with poor data understanding and preparation.Clean data, ...