Causal predictive modeling of survival of lung and bronchus cancer patients diagnosed during 2010–2011 in Texas

Understanding lung and bronchus cancer survival using advanced causal inference and predictive modeling techniques, highlights the critical importance of early-stage diagnosis, showing that patients diagnosed at localized stages have a substantially higher survival probability. This research underscores the necessity of promoting early screening and equitable cancer care to improve survival rates and healthcare outcomes for lung and bronchus cancer patients.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2025-10-31
DOI
https://doi.org/10.1371/journal.pone.0333477
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Causal predictive modeling of survival of lung and bronchus cancer patients diagnosed during 2010–2011 in Texas

Manish K. Tripathi, Everardo Cobos, Tamer F. Oraby, Zeinab A. Mohamed et al.
PLoS ONE
Advanced Causal Inference Techniques
article

Causal predictive modeling of survival of lung and bronchus cancer patients diagnosed during 2010–2011 in Texas

Manish K. Tripathi, Everardo Cobos, Tamer F. Oraby, Zeinab A. Mohamed, Sidketa Ida Fofana
article en

Abstract

Understanding lung and bronchus cancer survival using advanced causal inference and predictive modeling techniques, highlights the critical importance of early-stage diagnosis, showing that patients diagnosed at localized stages have a substantially higher survival probability. This research underscores the necessity of promoting early screening and equitable cancer care to improve survival rates and healthcare outcomes for lung and bronchus cancer patients.

PLoS ONEVol. 20(10)
The University of Texas Rio Grande Valley (US), Oberlin College (US)
Openalex Percentile: Top 71%
Advanced Causal Inference Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Causal predictive modeling of survival of lung and bronchus cancer patients diagnosed during 2010–2011 in Texas — Manish K. Tripathi, Everardo Cobos, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS