Functional Data Analysis (FDA) is an increasingly central statistical framework that extends conventional data analysis to observations recorded as functions, curves or shapes. This approach ...
Molecular Correlates of Long-Term Response to Bevacizumab in Glioblastoma Recurrent nonkinase domain FGFR VUS variants were collected from the Catalog of Somatic Mutations in Cancer and their ...
We present one of the first comprehensive evaluations of predictive information derived from retinal fundus photographs, ...
For monoclonal antibodies (mAbs), traditional design space identification methods typically rely on expensive wet-lab experiments or in silico models that, for low-density data, need improvement. A ...
Researchers at the University of Michigan have developed a new method that brings quantum-level accuracy to molecular modeling, offering fresh insights into a widely used simulation approach in ...
Predictive risk scores created using administrative claims and publicly available social determinants of health data strongly ...
Prognostic Significance of Isolated Tumor Cells and the Role of Immunohistochemistry in Nodal Evaluation in Breast Cancer: A SEER-Based Analysis and Reappraisal We used Monte Carlo simulation methods ...
The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital ...
Deep-Learning Paradigm Achieves Global Precision in Nuclear Charge Density PredictionsThe charge density distribution of an atomic nucleus is a ...
Behavioral information from an Apple Watch, such as physical activity, cardiovascular fitness, and mobility metrics, may be more useful for determining a person's health state than just raw sensor ...
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