Evidence mapPaperPMID 36675973Full record

ReviewLife (Basel, Switzerland)2022

Artificial Intelligence and Precision Medicine: A New Frontier for the Treatment of Brain Tumors.

Anil K Philip, Betty Annie Samuel, Saurabh Bhatia, Shaden A M Khalifa, Hesham R El-Seedi

Open access · goldAbstract readReview
In one paragraph

Review in Life (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
7.3field-weighted citation impact, top 2% of its field
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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

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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

5 authors at 3 institutions in 3 countries.

Anil K PhilipSchool of Pharmacy, University of Nizwa, Birkat Al Mouz, Nizwa 616, Oman.ORCID 0000-0003-2960-330X
Betty Annie SamuelSchool of Pharmacy, University of Nizwa, Birkat Al Mouz, Nizwa 616, Oman.
Saurabh BhatiaNatural and Medical Science Research Center, University of Nizwa, Birkat Al Mouz, Nizwa 616, Oman.
Shaden A M KhalifaDepartment of Molecular Biosciences, The Wenner-Gren Institute, Stockholm University, S-106 91 Stockholm, Sweden.
Hesham R El-SeediInternational Research Center for Food Nutrition and Safety, Jiangsu University, Zhenjiang 212013, China.
University of Nizwa · OMJiangsu University · CNStockholm University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain tumors are a widespread and serious neurological phenomenon that can be life- threatening. The computing field has allowed for the development of artificial intelligence (AI), which can mimic the neural network of the human brain. One use of this technology has been to help researchers capture hidden, high-dimensional images of brain tumors. These images can provide new insights into the nature of brain tumors and help to improve treatment options. AI and precision medicine (PM) are converging to revolutionize healthcare. AI has the potential to improve cancer imaging interpretation in several ways, including more accurate tumor genotyping, more precise delineation of tumor volume, and better prediction of clinical outcomes. AI-assisted brain surgery can be an effective and safe option for treating brain tumors. This review discusses various AI and PM techniques that can be used in brain tumor treatment. These new techniques for the treatment of brain tumors, i.e., genomic profiling, microRNA panels, quantitative imaging, and radiomics, hold great promise for the future. However, there are challenges that must be overcome for these technologies to reach their full potential and improve healthcare.

Indexed as

artificial intelligencebrain tumorsgene targetingimaging technologypatient careprecision medicine

Identifiers

PMID36675973
PMCPMC9866715
OpenAlexW4312186578

What Socratic holds

Textmetadata
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 Socratic graph.