Science Daily

Artificial intelligence: Algorithms improve medical image analysis

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 ...
ascopubs.org

Development of Machine Learning Algorithms Incorporating Electronic Health Record Data, Patient-Reported Outcomes, or Both to Predict Mortality for Outpatients With Cancer

shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area We trained and validated two-phase ML ...
Nature

Data Clustering Algorithms and Methods

Data clustering remains an essential component of unsupervised learning, enabling the exploration and interpretation of complex datasets. The field has witnessed considerable advancements that address ...
ascopubs.org

Development and Optimization of a Bladder Cancer Algorithm Using SEER-Medicare Claims Data

Categorizing patients with cancer by their disease stage can be an important tool when conducting administrative claims-based studies. As claims databases frequently do not capture this information, ...
Linux Journal

Unlocking Data Science Potential Understanding Machine Learning and Data Analysis with JupyterLab

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...