Reinforcement learning improves execution quality in financial markets

Alex Chen's adaptive execution framework, using reinforcement learning, cuts trading costs and improves market visibility.
European Medical Journal

Machine Learning Links Gut Microbiome to Improved DVT Detection

AI model suggests deep vein thrombosis may be identified more accurately using gut microbiome profiles. Read more.
IEEE

Enhancing Phishing Detection: A Machine Learning Approach With Feature Selection and Deep Learning Models

Abstract: With the rise in cybercrime, phishing remains a significant concern as it targets individuals with fake websites, causing victims to disclose their private information. The effective ...
Frontiers

Machine learning-based determination of sex-related bladder cancer biomarkers

Bladder cancer exhibits sex-specific behavior, occurring more frequently in males but progressing to advanced stages more commonly in females. The activation of sex hormone receptors may explain these ...
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% ...
Frontiers

Advanced machine learning techniques reveal multidimensional EEG abnormalities in children with ADHD: a framework for automatic diagnosis

Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder that affects attention, impulse control, and multitasking abilities in children and adults. Understanding ...
GitHub

Precise: Predictive Response Analysis from Single-Cell Expression

Precise is a Python-based computational framework for analyzing single-cell RNA sequencing (scRNA-seq) data to predict immune checkpoint inhibitor (ICI) responses. It integrates advanced feature ...
IEEE

Partition-Level Tensor Learning-Based Multiview Unsupervised Feature Selection

Abstract: Multiview unsupervised feature selection is an emerging direction in the machine learning community because of its ability to identify informative patterns and reduce the dimensionality of ...