Machine learning for artemisinin resistance in malaria treatment across

Hanrui Zhang, Jiantao Guo, Hongyang Li, Yuanfang Guan

Abstract read

In one paragraph

Article in iScience, 2022. 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.

Addressing infectious diseases in Africa by accelerating drug discovery through data science.Communications medicine · 2025
Review
Out-of-Distribution Detection as a Risk-Control Strategy for Medical Classification Machine Learning Models.Clinical and translational science · 2025
Article
First, Do No Harm: Addressing AI's Challenges With Out-of-Distribution Data in Medicine.Clinical and translational science · 2025
Article
Protocol for using Ciclops to build models trained on cross-platform transcriptome data for clinical outcome prediction.STAR protocols · 2022
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

4 authors.

Hanrui ZhangDepartment of Computational Medicine and Bioinformatics, The University of Michigan Medical School, Ann Arbor, MI 48109, USA.

Jiantao GuoDepartment of Computational Medicine and Bioinformatics, The University of Michigan Medical School, Ann Arbor, MI 48109, USA.

Hongyang LiDepartment of Computational Medicine and Bioinformatics, The University of Michigan Medical School, Ann Arbor, MI 48109, USA.

Yuanfang GuanDepartment of Computational Medicine and Bioinformatics, The University of Michigan Medical School, Ann Arbor, MI 48109, USA.

Funding

Machine Learning for Drug Response PredictionR35GM133346 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Yuanfang Guan · 2019 to 2026

$3.2M

NIGMS NIH HHS R35 GM133346

6 · The paper itself

Abstract

Drug resistance has been rapidly evolving with regard to the first-line malaria treatment, artemisinin-based combination therapies. It has been an open question whether predictive models for this drug resistance status can be generalized across

Indexed as

Artificial intelligenceBioinformaticsMicrobiology parasitePharmaceutical science

Identifiers

PMID35243261

DOI10.1016/j.isci.2022.103910

PMCPMC8873607

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.