Evidence map›Paper›PMID 41761338›Full record

ArticleJournal of cheminformatics2026

Privileged structure-based molecular fingerprints for organic electronic materials: towards intuitive machine learning interpretation.

Tae Wook Yang, Seung Hyun Jo, Min Chul Suh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cheminformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tae Wook YangOrganic Electronic Materials Laboratory, Department of Information Display, College of Science, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Korea.
Seung Hyun JoOrganic Electronic Materials Laboratory, Department of Information Display, College of Science, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Korea.
Min Chul SuhOrganic Electronic Materials Laboratory, Department of Information Display, College of Science, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Korea. mcsuh@khu.ac.kr.ORCID http://orcid.org/0000-0002-1295-1693

Funding

Ministry of Science and ICT, Korea 2021R1A2C1008725Ministry of Trade, Industry and Energy, Korea RS-2024-00418116
6 · The paper itself

Abstract

Molecular descriptors are central to the performance and interpretability of QSPR models, yet most existing fingerprints for organic electronics lack chemical relevance or interpretability. Here, we present the Organic Electronic Fingerprint (OEFP), a structure-based representation tailored for OLED and OPV materials. OEFP was constructed from a manually curated OLED dataset and publicly available OPV and chromophore datasets to ensure structural diversity. Synthetically accessible substructures were identified using fragmentation and ring decomposition methods, which capture the conjugated π-bonds crucial for organic electronic materials, and subsequently encoded as individual bits. In case studies of OPV HOMO energy prediction, OEFP achieved up to 13.7% lower MAE and 1.6% higher R

Indexed as

Machine learningMolecular fingerprintOrganic electronic materialsOrganic light-emitting diode (OLED)Organic photovoltaics (OPV)

Identifiers

PMID41761338
PMCPMC12955134

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.