Cover Image

Intercept Cancer: Cancer Pre-Screening with Large Scale Healthcare Foundation Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sun, Liwen, Yao, Hao-Ren, Gao, Gary, Frieder, Ophir, Xiong, Chenyan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AMNESIA: A Large Scale Medical Unlearning Benchmark Suite with Disease-Informed Analysis
by: Davoudi, Saeedeh, et al.
Published: (2026)

ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance
by: Sun, Liwen, et al.
Published: (2024)

TARAZ: Persian Short-Answer Question Benchmark for Cultural Evaluation of Language Models
by: Iranmanesh, Reihaneh, et al.
Published: (2026)

FLAME-MoE: A Transparent End-to-End Research Platform for Mixture-of-Experts Language Models
by: Kang, Hao, et al.
Published: (2025)

RePro: Training Language Models to Faithfully Recycle the Web for Pretraining
by: Yu, Zichun, et al.
Published: (2025)

Generating Pretraining Tokens from Organic Data for Data-Bound Scaling
by: Yu, Zichun, et al.
Published: (2026)

MATES: Model-Aware Data Selection for Efficient Pretraining with Data Influence Models
by: Yu, Zichun, et al.
Published: (2024)

AutoRule: Reasoning Chain-of-thought Extracted Rule-based Rewards Improve Preference Learning
by: Wang, Tevin, et al.
Published: (2025)

InferCept: Efficient Intercept Support for Augmented Large Language Model Inference
by: Abhyankar, Reyna, et al.
Published: (2024)

Model Merging in Pre-training of Large Language Models
by: Li, Yunshui, et al.
Published: (2025)

Montessori-Instruct: Generate Influential Training Data Tailored for Student Learning
by: Li, Xiaochuan, et al.
Published: (2024)

Self-supervised Representation Learning on Electronic Health Records with Graph Kernel Infomax
by: Yao, Hao-Ren, et al.
Published: (2022)

Toward Understanding BERT-Like Pre-Training for DNA Foundation Models
by: Liang, Chaoqi, et al.
Published: (2023)

Perplexity-Aware Data Scaling Law: Perplexity Landscapes Predict Performance for Continual Pre-training
by: Liu, Lei, et al.
Published: (2025)

Joint Selection for Large-Scale Pre-Training Data via Policy Gradient-based Mask Learning
by: Fan, Ziqing, et al.
Published: (2025)

Large Language Models for Mathematicians
by: Frieder, Simon, et al.
Published: (2023)

Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model
by: Rahman, Salman, et al.
Published: (2024)

Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models
by: Zhang, Jingyang, et al.
Published: (2024)

Training Large Reasoning Models Efficiently via Progressive Thought Encoding
by: Zhang, Zeliang, et al.
Published: (2026)

Group-Level Data Selection for Efficient Pretraining
by: Yu, Zichun, et al.
Published: (2025)

HLAT: High-quality Large Language Model Pre-trained on AWS Trainium
by: Fan, Haozheng, et al.
Published: (2024)

GeoNorm: Unify Pre-Norm and Post-Norm with Geodesic Optimization
by: Zheng, Chuanyang, et al.
Published: (2026)

Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization
by: Samragh, Mohammad, et al.
Published: (2024)

Enhancing Hepatopathy Clinical Trial Efficiency: A Secure, Large Language Model-Powered Pre-Screening Pipeline
by: Gui, Xiongbin, et al.
Published: (2025)

Fact-Aware Multimodal Retrieval Augmentation for Accurate Medical Radiology Report Generation
by: Sun, Liwen, et al.
Published: (2024)

FineInstructions: Scaling Synthetic Instructions to Pre-Training Scale
by: Patel, Ajay, et al.
Published: (2026)

SVFit: Parameter-Efficient Fine-Tuning of Large Pre-Trained Models Using Singular Values
by: Sun, Chengwei, et al.
Published: (2024)

nanoLM: an Affordable LLM Pre-training Benchmark via Accurate Loss Prediction across Scales
by: Yao, Yiqun, et al.
Published: (2023)

Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure
by: Chen, Ziyi, et al.
Published: (2024)

Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference
by: Song, Yuxuan, et al.
Published: (2025)

Foundations of Large Language Models
by: Xiao, Tong, et al.
Published: (2025)

AutoScale: Scale-Aware Data Mixing for Pre-Training LLMs
by: Kang, Feiyang, et al.
Published: (2024)

Exploring Scaling Laws for EHR Foundation Models
by: Zhang, Sheng, et al.
Published: (2025)

Theoretical Foundations of Scaling Law in Familial Models
by: Song, Huan, et al.
Published: (2025)

Distilling Multi-Scale Knowledge for Event Temporal Relation Extraction
by: Yao, Hao-Ren, et al.
Published: (2022)

Foundations of Large Language Model Compression -- Part 1: Weight Quantization
by: Young, Sean I.
Published: (2024)

MIA-Tuner: Adapting Large Language Models as Pre-training Text Detector
by: Fu, Wenjie, et al.
Published: (2024)

CMR Scaling Law: Predicting Critical Mixture Ratios for Continual Pre-training of Language Models
by: Gu, Jiawei, et al.
Published: (2024)

Efficient Knowledge Probing of Large Language Models by Adapting Pre-trained Embeddings
by: Sharma, Kartik, et al.
Published: (2025)

Pre-trained Large Language Models Use Fourier Features to Compute Addition
by: Zhou, Tianyi, et al.
Published: (2024)