On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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4 results for “510(k)”

Harmonizing Safety and Speed: A Human-Algorithm Approach to Enhance the FDA's Medical Device Clearance Policycs.LG

Paper proposes a human-algorithm approach to reduce medical device recall risk and workload.

problem High recall rate and regulatory workload in FDA's 510(k) pathway.

method Developed machine learning models to estimate recall risk and proposed a data-driven clearance policy.

result Conservative evaluation of policy shows a 32.9% improvement in recall rate and 40.5% reduction in workload.

FDA 510(k)medical devices recall workload

2024-07-16abs ↗pdf ↗

A Floquet-Liapunov theorem in Frechet spacesmath.CA

In this paper we prove a variation of the theorem in title, for equations with periodic coefficients, in Frechet spaces. The main result gives equivalent conditions ensuring the reduction of such an equation to one with constant coefficient. In the particular case of $C^{\infty}$ , we obtain the exact analogue of the cl…

1999-01-12abs ↗pdf ↗

Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Imageseess.IV

Enhanced deep learning model improves tumor segmentation in ultrasound images.

problem Challenges in integrating patient-specific medical priors into deep learning models.

method Integrates visual saliency into a U-Net architecture with attention blocks.

result Achieved a Dice similarity coefficient of 90.5 percent on a dataset of 510 images.

Deep Learning Tumor Segmentation Ultrasound Imaging Visual Saliency Attention Mechanism

2019-10-20abs ↗pdf ↗

Outcome-Classified Precision Auditing of Filter Rules in Algorithmic DEX Trading: Evidence from 2,400 Rejection Eventsq-fin.TR

The paper audits trading filters, finding a high save-to-miss ratio.

problem Improving the efficiency and accuracy of trading filters in decentralized exchanges.

method A precision audit of filter rules against real trading data, classifying rejection events.

result Conservative save-to-miss ratio of 3.7 : 1, with wider interpretation of 14.8 : 1.

Decentralized Exchanges Trading Filters Precision Audit Save-to-Miss Ratio Rug-Pull Risk

2026-07-02abs ↗pdf ↗