Evidence map›Paper›PMID 40453101›Full record

ArticleAdvances in neural information processing systems2024

Mason Hargrave, Alex Spaeth, Logan Grosenick

Abstract read
In one paragraph

Article in Advances in neural information processing systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mason HargraveCenter for Studies in Physics and Biology, The Rockefeller University, New York, NY, USA.
Alex SpaethDept. of Electrical and Computer Engineering, University of California, Santa Cruz, Santa Cruz, CA, USA.
Logan GrosenickDept. of Psychiatry and BMRI, Weill Cornell Medicine, Cornell University, New York, NY, USA.

Funding

Efficacy of biomarker-guided rTMS for treatment resistant depressionR01MH118388 · NIMH · WEILL MEDICAL COLL OF CORNELL UNIV · PI BHATI, MAHENDRA T, GUNNING, FAITH M · 2019 to 2025
$6.2M
Scalable Biomarkers and Generative Digital Twins for Personalized Neurostimulation in DepressionR01MH131534 · NIMH · WEILL MEDICAL COLL OF CORNELL UNIV · PI LOGAN GROSENICK · 2022 to 2026
$3.2M
NIMH NIH HHS R01 MH118388NIMH NIH HHS R01 MH131534
6 · The paper itself

Abstract

Healthcare applications pose significant challenges to existing reinforcement learning (RL) methods due to implementation risks, limited data availability, short treatment episodes, sparse rewards, partial observations, and heterogeneous treatment effects. Despite significant interest in using RL to generate dynamic treatment regimes for longitudinal patient care scenarios, no standardized benchmark has yet been developed. To fill this need we introduce

Identifiers

PMID40453101
PMCPMC12124763

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.