Evidence map›Paper›PMID 40199295›Full record

ReviewYearbook of medical informatics2024

Cancer Informatics: Novel Methods and Applications of Artificial Intelligence in Cancer Care Delivery.

Sanjay Aneja, Ravi B Parikh

Abstract readReview
In one paragraph

Review in Yearbook of medical informatics, 2024. 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

2 authors.

Sanjay AnejaYale Cancer Center, New Haven, CT, USA.
Ravi B ParikhAbramson Cancer Center, Philadelphia, PA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo summarize significant research contributions on cancer informatics published in 2023, an extensive search using PubMed/MEDLINE was conducted to identify the scientific contributions published in 2023 that address topics in cancer. The selection process comprised three steps: (i) ten candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of three best papers was conducted by the editorial board of the Yearbook.

resultsThe two selected papers demonstrate advances in the clinical implementation of cancer informatics methodologies. Both studies highlight translation of informatics methodologies to improve cancer outcomes.

conclusionsCancer informatics is a maturing subfield of bioinformatics. As novel methodologies continue to emerge, further emphasis will be placed on rigorous clinical validation and real-world scalability of such solutions to positively impact patient outcomes.

Indexed as

Artificial IntelligenceMedical InformaticsNeoplasmsDelivery of Health CareHumans

Identifiers

PMID40199295
PMCPMC12020643

What OpenQuestion 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 OpenQuestion graph.