SurvBench supplies a configurable, open-source preprocessing pipeline that standardizes multi-modal EHR data from four critical-care databases for single-risk and competing-risk survival analysis.
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4 Pith papers cite this work. Polarity classification is still indexing.
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Gated-CNN applies independent 1D convolutions and sigmoid gating to IMU streams from smartwatches, achieving 90-93% F1 on five datasets and 97% F1 with zero missed falls in real-time Pixel Watch testing, outperforming Transformer baselines.
PBE-UNet adds scale-aware aggregation and progressive boundary expansion modules to U-Net and reports better segmentation performance than prior methods on four ultrasound datasets.
GPU implementation of global optimization for logic model identification from time-course data achieves 33-1866% speedups over CPU baselines on two example regulatory networks.
citing papers explorer
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SurvBench: A Standardised Preprocessing Pipeline for Multi-Modal Electronic Health Record Survival Analysis
SurvBench supplies a configurable, open-source preprocessing pipeline that standardizes multi-modal EHR data from four critical-care databases for single-risk and competing-risk survival analysis.
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You Don't Need Attention: Gated Convolutional Modeling for Watch-Based Fall Detection
Gated-CNN applies independent 1D convolutions and sigmoid gating to IMU streams from smartwatches, achieving 90-93% F1 on five datasets and 97% F1 with zero missed falls in real-time Pixel Watch testing, outperforming Transformer baselines.
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PBE-UNet: A light weight Progressive Boundary-Enhanced U-Net with Scale-Aware Aggregation for Ultrasound Image Segmentation
PBE-UNet adds scale-aware aggregation and progressive boundary expansion modules to U-Net and reports better segmentation performance than prior methods on four ultrasound datasets.
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GPU-accelerated Modeling of Biological Regulatory Networks
GPU implementation of global optimization for logic model identification from time-course data achieves 33-1866% speedups over CPU baselines on two example regulatory networks.