Evidence map›Paper›PMID 34138457›Full record

ArticleAdvances in experimental medicine and biology2022

Artificial Intelligence and Precision Medicine: A Perspective.

Jacek Lorkowski, Oliwia Kolaszyńska, Mieczysław Pokorski

Abstract read
PubMed Publisher
In one paragraph

Article in Advances in experimental medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Symmetry and asymmetry in atherosclerosis.International journal of occupational medicine and environmental health · 2023
    Review
  5. Review
  6. Article
  7. Human Recombinant DNase I (PulmozymeInternational journal of molecular sciences · 2021
    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

3 authors.

Jacek LorkowskiDepartment of Orthopedics, Traumatology and Sports Medicine, Central Clinical Hospital of the Ministry of Internal Affairs and Administration, Warsaw, Poland. jacek.lorkowski@gmail.com.ORCID https://orcid.org/0000-0001-5985-9790
Oliwia KolaszyńskaDepartment of Cardiology, Independent Public Regional Hospital, Szczecin, Poland.ORCID https://orcid.org/0000-0002-7543-7990
Mieczysław PokorskiInstitute of Health Sciences, Opole University, Opole, Poland.ORCID https://orcid.org/0000-0002-8710-9775

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article aims to present how the advanced solutions of artificial intelligence and precision medicine work together to refine medical management. Multi-omics seems the most suitable approach for biological analysis of data on precision medicine and artificial intelligence. We searched PubMed and Google Scholar databases to collect pertinent articles appearing up to 5 March 2021. Genetics, oncology, radiology, and the recent coronavirus disease (COVID-19) pandemic were chosen as representative fields addressing the cross-compliance of artificial intelligence (AI) and precision medicine based on the highest number of articles, topicality, and interconnectedness of the issue. Overall, we identified and perused 1572 articles. AI is a breakthrough that takes part in shaping the Fourth Industrial Revolution in medicine and health care, changing the long-time accepted diagnostic and treatment regimens and approaches. AI-based link prediction models may be outstandingly helpful in the literature search for drug repurposing or finding new therapeutical modalities in rapidly erupting wide-scale diseases such as the recent COVID-19.

Indexed as

Artificial IntelligenceCOVID-19Drug RepositioningHumansPandemicsPrecision MedicineArtificial intelligenceCOVID-19GeneticsHealth careMulti-omicsPrecision medicineRadiology

Identifiers

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.