Evidence map›Paper›PMID 37622839›Full record

Trial reportAdvances in respiratory medicine2023

A Machine Learning-Based Model to Predict In-Hospital Mortality of Lung Cancer Patients: A Population-Based Study of 523,959 Cases.

Que N N Tran, Minh-Khang Le, Tetsuo Kondo, Takeshi Moriguchi

Open access · goldAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Advances in respiratory medicine, 2023. 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
0.8field-weighted citation impact, top 24% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

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

4 authors at 1 institution in 1 country.

Que N N TranEmergency & Critical Care Medicine Department, Graduate School of Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi Prefecture, 1110 Shimokato, Chuo City 409-3898, Japan.
Minh-Khang LePathology Department, Graduate School of Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi Prefecture, 1110 Shimokato, Chuo City 409-3898, Japan.
Tetsuo KondoPathology Department, Graduate School of Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi Prefecture, 1110 Shimokato, Chuo City 409-3898, Japan.
Takeshi MoriguchiEmergency & Critical Care Medicine Department, Graduate School of Medicine, Faculty of Medicine, University of Yamanashi, Yamanashi Prefecture, 1110 Shimokato, Chuo City 409-3898, Japan.ORCID 0000-0002-7515-4173
University of Yamanashi · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Adenocarcinoma of LungCarcinoma, Non-Small-Cell LungLung NeoplasmsHospital MortalityHumansMachine Learningin-hospital mortalitylung cancermodel trainingpatient-centered strategyrisk stratification

Identifiers

PMID37622839
PMCPMC10451707
OpenAlexW4385704344

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.