[Paper Reading] Reinforcement Learning for Tumor Segmentation & Biomarker Discovery

​This week, we will walk through and discuss the paper:
Reinforcement Learning for Tumor Segmentation & Biomarker Discovery
[https://www.kaggle.com/code/achievement/imaging-mri-segmentation-molecular-analysis]

​Traditional AI-based tumor segmentation models, such as YOLO 11, YOLO+SAM2, Fluorescence 2 and Detectron 2, etc often struggle with over-segmentation and false negatives due to their static nature. The research introduces Reinforcement Learning (GRPO & PPO) to iteratively refine segmentation masks, improving recall, boundary precision, and clinical reliability. Additionally, multi-omics biomarker discovery is integrated, correlating segmentation outputs with molecular markers to enhance precision medicine approaches.

​Speaker: Fae Gaze

​A Machine Learning/AI Data Scientist, Biostatistician, and Bioinformatician with over 8 years of experience working on diverse projects for companies and research institutions. Her expertise spans text classification, transformers, deep learning, cloud computing, and computational biology. Her mission is to apply advanced AI and statistical techniques to solve complex computational problems in biomedical research, genomic medicine, and data-driven systems.

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​About SupportVectors AI Meetup:
We are a group of applied AI practitioners and enthusiasts who have formed a collective learning community. Every Wednesday evening at PM PST, we hold our research paper reading seminar covering an AI topic. One member carefully explains the paper, making it more accessible to a broader audience. Then, we follow this reading with a more informal discussion and socializing.

​​You are welcome to join this in person or over Zoom. SupportVectors is an AI training lab located in Fremont, CA, close to Tesla and easily accessible by road and BART. We follow the weekly sessions with snacks, soft drinks, and informal discussions.