Evidence map›Paper›PMID 42797456›Full record

ArticlePharmaceuticals (Basel, Switzerland)2026

An Explainable Machine Learning-Based QSAR Framework for Predicting Thrombin Inhibitory Activity.

Ali Onur Kaya, Mert Can Emre

Abstract read
In one paragraph

Article in Pharmaceuticals (Basel, Switzerland), 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

2 authors.

Ali Onur KayaRadiotherapy Department, Health Services Vocational School, Akdeniz University, 07070 Antalya, Türkiye.ORCID 0000-0003-4220-1866
Mert Can EmreMotor Vehicles Department, Sorgun Vocational School, Yozgat Bozok University, 66000 Yozgat, Türkiye.ORCID 0000-0002-1445-0358

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

drug discoveryensemble learningexplainable artificial intelligencequantitative structure–activity relationship (QSAR)thrombin inhibitors

Identifiers

PMID42797456
PMCPMC13610635

What OpenQuestion holds

Textmetadata
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.