Analyzing thousands of proteins from a single drop of blood is no longer science fiction. High-throughput proteomics has transformed biomarker discovery by enabling simultaneous profiling of thousands ...

MMER is a flexible Python framework for multivariate mixed-effects regression. Its defining feature is a plug-and-play architecture that allows you to seamlessly integrate any generic regressor to ...

DCE-MRI for assessment of pathologic complete response after completion of neoadjuvant therapy in triple-negative breast cancer patients. This is an ASCO Meeting Abstract from the 2026 ASCO Annual ...

Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...

Pregnancy of uncertain viability affects up to 30% of early pregnancies. Among women presenting with per-vaginal bleeding and absence of a fetal pole, prognosis remains indeterminate. The lack of ...

Introduction The number of children with life-limiting conditions has risen in recent decades, partly due to medical advances ...

This valuable study introduces a model to help researchers understand how multivariate processes affect observed relationships in genetic data. The authors provide a tool to estimate model parameters.

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Background: Aspiration pneumonia is a serious complication after cardiac surgery, particularly among older patients. Preoperative oral frailty—decline in oral function including poor hygiene and ...

Across the literature, multivariable models for predicting giant cell arteritis diagnoses showed various methodological weaknesses. Multivariable models can aid in the diagnosis of giant cell ...

ABSTRACT: Bipolar disorder is a multifaceted psychiatric illness characterized by unpredictable mood episodes and highly variable treatment responses across individuals. Predicting response to ...