Frontiers

Machine learning–guided feature selection and predictive model construction for attention-deficit/hyperactivity disorder

Background: Attention Deficit/Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental disorder, but its diagnosis remains constrained. This study aimed to identify potential candidate ...
Targeted Oncology

Machine Learning Model May Optimize Treatment Selection and Survival in HCC

The ML model stratifies HCC patients by mortality risk, guiding treatment decisions between liver transplantation and surgical resection. The model demonstrated improved survival outcomes, with a 54% ...
ascopubs.org

Bayesian Counterfactual Machine Learning Individualizes Radiation Modality Selection to Mitigate Immunosuppression

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...
IEEE

What is the Value of Heuristic Model Selection and Aggregation in Federated Learning?

Abstract: Federated learning (FL) is a promising distributed machine learning framework for mobile networks, where an aggregation server produces a global model by aggregating the local models from ...
Frontiers

Construction and validation of a machine learning based prognostic prediction model for children with traumatic brain injury

Department of Pediatrics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Hennan, China Objective: This study aimed to establish a prediction model for the short-term prognosis of ...
News Medical

Machine learning model guides smarter gene selection in newborn screening

More than a decade ago, researchers launched the BabySeq Project, a pilot program to return newborn genomic sequencing results to parents and measure the effects on newborn care. Today, over 30 ...
IEEE

Variability-Aware Machine Learning Model Selection: Feature Modeling, Instantiation, and Experimental Case Study

Abstract: The emergence of machine learning (ML) has led to a transformative shift in software techniques and guidelines for building software applications that support data analysis process ...