Bone Marrow Transplantation - Application of machine learning algorithms for clinical predictive modeling: a data-mining approach in SCT Skip to main content Thank you for visiting nature.com.

We laud the authors of a recent CMAJ article for their usable framework for the development and adoption of machine-learned solutions1 and propose that this will be useful to guide the use of machine ...

Machine learning (ML) has the potential to transform oncology and, more broadly, medicine. 1 The introduction of ML in health care has been enabled by the digitization of patient data, including the ...

How do patient-reported outcomes improve machine learning algorithms to predict mortality in cancer? ... Secondary analysis of a randomized clinical trial. PLoS One 17:e0267012, 2022. ... Data ...

The goal of implementing artificial intelligence and machine learning in clinical research is not to replace humans with digital tools but to increase their productivity. By Gary Shorter on May 17 ...

Apart from simple diagnosis, the study takes an important step toward predictive health monitoring by modeling the risk of ...

Study: From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment. Image Credit: Have a nice day Photo / Shutterstock.com. Common ML models in ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...