The application of advanced statistical methods in infectious diseases has never been more pertinent than during the recent COVID-19 pandemic. Traditional ...

Abstract: Following on the first part of our review of synthetic aperture radar (SAR) image statistical modeling [1], which concerns single-pixel statistical models, this article extends our ...

Abstract: Frequentist statistical methods, such as hypothesis testing, are standard practices in studies that provide benchmark comparisons. Unfortunately, these methods have often been misused, e.g., ...

New research provides evidence that while advanced artificial intelligence models process language with remarkable skill, ...

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Anupam Ojha, a postdoctoral fellow at the Flatiron Institute, develops advanced statistical frameworks to bridge the gap ...

The inaugural season of the Gomezgil Yaspik Data Science Laboratory marks the beginning of a new chapter for for Bowdoin.

Scientists discovered that atmospheric rivers reaching Antarctica arrive at an angle, improving snowfall tracking and sea ...

Biopharmaceutical developers should introduce risk-based, phase-appropriate characterization strategies for quality control ...

Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

Upcoming Type B Statistical Methods Meeting expected to set stage for FDA to align with EMA and MHRA on use of Fall 2026 ...

Causal inference is the task of drawing conclusions from data about the effects of treatments and other type of interventions. In epidemiology and clinical research, as well as in many other fields, ...