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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.

169,051 papers · 148 categories

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6 results for “vasopressors”

Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Scorecs.LG

The paper learns personalized treatment rules from observational data.

problem Developing effective treatment policies for individual patients.

method Contextual bandit approach to minimize expected risk of treatment policies.

result The proposed method outperforms physicians and baseline approaches in IV and VP administration.

individualized treatment rules contextual bandit inverse propensity score observational data intravenous fluids

2020-07-02abs ↗pdf ↗

Withholding or withdrawing invasive interventions may not accelerate time to death among dying ICU patientscs.CY

Invasive interventions did not significantly shorten ICU patients' time to death.

problem Determining if withholding or withdrawing invasive interventions affects ICU patients' time to death.

method Observational study using MIMIC-III ICU database, stratifying by severity, comparing 2002-2005 vs. 2008-2011.

result Despite a reduction in invasive interventions, time to death did not decrease.

ICU patients invasive interventions time to death vasopressors non-invasive ventilation

2018-08-04abs ↗pdf ↗

Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learningstat.ML

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.

Reinforcement Learning Hypotension Critical Care Electronic Health Records Treatment Options

2020-01-09abs ↗pdf ↗

Predicting Mortality Risk in Viral and Unspecified Pneumonia to Assist Clinicians with COVID-19 ECMO Planningstat.AP

Develops a risk score to assist ECMO planning for critically ill patients with viral or unspecified pneumonia.

problem Lack of a risk score to guide ECMO planning for critically ill patients.

method Leverages machine learning to develop the PEER score.

result PEER score predicts mortality and decompensation in patients eligible for ECMO.

COVID-19 ECMO Pneumonia Risk Score Machine Learning

2020-06-02abs ↗pdf ↗

Sepsis World Model: A MIMIC-based OpenAI Gym "World Model" Simulator for Sepsis Treatmentcs.LG

Simulates sepsis treatment decisions using a world model approach.

problem Predicting optimal sepsis treatment actions based on noisy EHR data.

method Uses a Variational Auto-Encoder and Mixture Density Network (MDN-RNN) to model sepsis patient trajectories.

result Simulator learns from MIMIC dataset to predict patient states.

sepsis world model MIMIC OpenAI Gym MDN-RNN

2019-12-15abs ↗pdf ↗

Clinical characteristics, complications and outcomes of critically ill patients with Dengue in Brazil, 2012-2024: a nationwide, multicentre cohort studystat.ML

Study describes severe dengue ICU patients in Brazil, 2012-2024.

problem Characterize severe dengue ICU patients and identify risk factors.

method Prospective study, descriptive statistics, logistic regression, machine learning.

result Advanced age, comorbidities, leukocytes, and platelets are significant risk factors for complications.

dengue ICU Brazil complications risk factors

2025-08-25abs ↗pdf ↗