Evidence map›Paper›PMID 33560998›Full record

ArticleJournal of medical Internet research2021

Artificial Intelligence-Aided Precision Medicine for COVID-19: Strategic Areas of Research and Development.

Enrico Santus, Nicola Marino, Davide Cirillo, Emmanuele Chersoni, Arnau Montagud, Antonella Santuccione Chadha, Alfonso Valencia, Kevin Hughes, Charlotta Lindvall

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  5. LitCovid ensemble learning for COVID-19 multi-label classification.Database : the journal of biological databases and curation · 2022
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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

9 authors.

Enrico SantusDivision of Decision Science and Advanced Analytics, Bayer Pharmaceuticals, Whippany, NJ, United States.ORCID 0000-0002-7327-2731
Nicola MarinoThe Women's Brain Project, Zurich, Switzerland.ORCID 0000-0001-7510-1939
Davide CirilloThe Women's Brain Project, Zurich, Switzerland.ORCID 0000-0003-4982-4716
Emmanuele ChersoniDepartment of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong, China (Hong Kong).ORCID 0000-0001-8742-0451
Arnau MontagudBarcelona Supercomputing Center, Barcelona, Spain.ORCID 0000-0002-7696-1241
Antonella Santuccione ChadhaThe Women's Brain Project, Zurich, Switzerland.ORCID 0000-0002-4021-3129
Alfonso ValenciaBarcelona Supercomputing Center, Barcelona, Spain.ORCID 0000-0002-8937-6789
Kevin HughesMassachusetts General Hospital, Boston, MA, United States.ORCID 0000-0003-4084-6484
Charlotta LindvallDana-Farber Cancer Institute, Boston, MA, United States.ORCID 0000-0003-2090-2039

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) technologies can play a key role in preventing, detecting, and monitoring epidemics. In this paper, we provide an overview of the recently published literature on the COVID-19 pandemic in four strategic areas: (1) triage, diagnosis, and risk prediction; (2) drug repurposing and development; (3) pharmacogenomics and vaccines; and (4) mining of the medical literature. We highlight how AI-powered health care can enable public health systems to efficiently handle future outbreaks and improve patient outcomes.

Indexed as

Artificial IntelligenceCOVID-19HumansPandemicsPrecision MedicineResearchSARS-CoV-2artificial intelligenceCOVID-19epidemicliteraturemonitoringpandemicpersonalized medicineprecision medicinepreventionpublic healthSARS-CoV-2

Identifiers

PMID33560998
PMCPMC7958975

What OpenQuestion holds

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LicenceCC BY
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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.