Evidence map›Paper›PMID 42454932›Full record

ArticleMicrobiology spectrum2026

Construction and validation of a phenotypic prediction model for bacterial gentamicin resistance using deep learning with gene sequences.

Jun Li, Siyan Xue, Lingxuan Hou, Zhixuan Zhang, Kaixuan Yuan, Xiaozhong Chen, Chui Kong, Liyang Wang, Bing Gu, Xiaoxiao Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microbiology spectrum, 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

10 authors.

Jun Li *Laboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Siyan Xue *School of Biomedical Engineering, Tsinghua University, Beijing, China.
Lingxuan Hou *Optical Bioimaging Laboratory, Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Zhixuan ZhangLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Kaixuan YuanLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.ORCID 0009-0004-9815-7846
Xiaozhong ChenLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Chui KongSchool of Information Science and Technology, Fudan University, Shanghai, China.ORCID 0000-0002-3855-5867
Liyang WangSchool of Biomedical Engineering, Tsinghua University, Beijing, China.
Bing GuLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.ORCID 0000-0001-7764-3213
Xiaoxiao LiuLaboratory Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.ORCID 0000-0001-9401-9770

Funding

National Natural Science Foundation of China 82372298, 32170160
6 · The paper itself

Abstract

The emergence of bacterial resistance to antibiotics poses a significant threat to human health; thus, there is an urgent need for new strategies in understanding the mechanisms of resistance and further fast prediction of it. Deep learning models offer promising solutions through analyzing genetic sequences in the prediction of bacterial resistance patterns. This study develops and validates a transformer-based deep learning model, DNABERT-2-117M, to predict gentamicin resistance in

Indexed as

Anti-Bacterial AgentsDeep LearningDrug Resistance, BacterialGentamicinsKlebsiella pneumoniaeGenome, BacterialHumansKlebsiella InfectionsMicrobial Sensitivity TestsPhenotypePrediction AlgorithmsPredictive Learning ModelsAnti-Bacterial AgentsGentamicinsantibiotic resistancedeep learninggenomicKlebsiella pneumoniaeprediction model

Identifiers

PMID42454932
PMCPMC13436402

What OpenQuestion holds

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LicenceCC BY
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.