Evidence map›Paper›PMID 38795030›Full record

ArticleJournal of chemical theory and computation2024

Quantum-to-Classical Neural Network Transfer Learning Applied to Drug Toxicity Prediction.

Anthony M Smaldone, Victor S Batista

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

2 authors.

Anthony M SmaldoneDepartment of Chemistry, Yale University, New Haven 06511, Connecticut, United States.ORCID 0009-0008-7265-0017
Victor S BatistaDepartment of Chemistry, Yale University, New Haven 06511, Connecticut, United States.ORCID 0000-0002-3262-1237

Funding

Predoctoral Program in BiophysicsT32GM149438 · NIGMS · YALE UNIVERSITY · PI Yong Xiong, Elsa Chui Ying Yan · 2023 to 2026
$2.6M
NIGMS NIH HHS T32 GM149438
6 · The paper itself

Abstract

Toxicity is a roadblock that prevents an inordinate number of drugs from being used in potentially life-saving applications. Deep learning provides a promising solution to finding ideal drug candidates; however, the vastness of chemical space coupled with the underlying

Indexed as

Neural Networks, ComputerQuantum TheoryDeep LearningDrug-Related Side Effects and Adverse ReactionsMachine Learning

Identifiers

PMID38795030
PMCPMC12665360

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.