IEEE

MoRe-ERL: Learning Motion Residuals Using Episodic Reinforcement Learning

Abstract: We propose MoRe-ERL, a framework that combines Episodic Reinforcement Learning (ERL) and residual learning, which refines preplanned reference trajectories into safe, feasible, and efficient ...
ahajournals.org

Abstract 4371736: Residual Learning Networks for Automated Detection of Hypertensive Retinopathy: A Multi-Institutional Validation Study

Introduction: Cardiovascular-retinal pathophysiology represents an emerging frontier in precision medicine, with hypertensive retinopathy (HR) serving as a critical biomarker for systemic vascular ...
ascopubs.org

Machine Learning Model Integrating Computed Tomography Image–Derived Radiomics and Circulating miRNAs to Predict Residual Teratoma in Metastatic Nonseminoma Testicular Cancer

We retrospectively identified 111 lesions, divided into training and test sets (n = 78 v 33) with equal class distribution. 3D Slicer was used to segment lesions with a short axis of >10 mm from the ...
ascopubs.org

Preliminary deep learning model to predict residual tumor in advanced epithelial ovarian cancer.

Utility of deep versatile classifier for accurate subtyping of lung adenocarcinoma using hematoxylin-eosin images. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract ...
The New York Times

How A.I. Can Revive a Love of Learning

Modern technology offers new possibilities for transforming teaching. By Anant Agarwal Anant Agarwal is an education innovator. This personal reflection is part of a series called Turning Points, in ...