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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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0111 · Nov 201819922001200920172026
7 results for Hypotension

SODA-RL learns diverse treatment options for hypotension from data.

problem Identifying the best treatment for acute hypotension from observational data.
method SODA-RL: Safely Optimized, Diverse, and Accurate Reinforcement Learning.
result SODA-RL identifies distinct, plausible treatment options from observational data.

Timely prediction of clinically critical events in Intensive Care Unit (ICU) is important for improving care and survival rate. Most of the existing approaches are based on the application of various classification methods on explicitly extracted statistical features from vital signals. In this work, we propose to elim…

2018-11-14abs ↗pdf ↗

A new CA-GAN architecture improves minority class data generation in health datasets.

problem Algorithmic bias due to health data poverty and underrepresentation of minority groups.
method Proposes CA-GAN architecture to address shortcomings of resampling and GAN-based approaches.
result CA-GAN outperforms SMOTE and WGAN-GP* in generating authentic minority class data and maintaining original distribution.

Method uses semi-supervised learning to estimate optimal treatment regimes from medical records.

problem Estimating optimal treatment regimes from electronic medical records.
method Imputation-based semi-supervised method using unlabeled data.
result Proposed method yields more efficient estimators of optimal treatment regimes.

Bayesian method estimates dynamics from near-optimal trajectories.

problem Estimating dynamics from near-optimal expert trajectories in reinforcement learning.
method Constraint-based Bayesian approach integrating expert near-optimality.
result Significant improvements in decision-making and transfer success.

PHASE predicts surgical complications from physiological signals.

problem Predicting adverse surgical outcomes from physiological signals.
method Self-supervised transfer learning for physiological signals.
result PHASE outperforms other approaches in predicting five surgical complications.