Direct Carbon Dioxide Emissions in Robotic Lung Resection–Analysis of a Prospective Cohort

Direct CO2 emissions in robotic lung resection may be lower than previously assumed. While strategies to reduce CO2 utilization ought to be pursued, future studies should be aimed at establishing the optimal approach to mitigating the environmental impact of robotic lung resection.

Authors

Institutions

Publication Details

Journal
Journal of Surgical Research
Published
2025-03-31
DOI
https://doi.org/10.1016/j.jss.2025.03.001
Citations
1
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.52

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Direct Carbon Dioxide Emissions in Robotic Lung Resection–Analysis of a Prospective Cohort

Waël C. Hanna, Ikennah Browne, Yogita S. Patel
1 citations
Journal of Surgical Research
Lung Cancer Diagnosis and Treatment
1.52
article

Direct Carbon Dioxide Emissions in Robotic Lung Resection–Analysis of a Prospective Cohort

Waël C. Hanna, Ikennah Browne, Yogita S. Patel
article en
1 citations

Abstract

Direct CO2 emissions in robotic lung resection may be lower than previously assumed. While strategies to reduce CO2 utilization ought to be pursued, future studies should be aimed at establishing the optimal approach to mitigating the environmental impact of robotic lung resection.

Journal of Surgical ResearchVol. 309
McMaster University (CA)
Canadian Association of Thoracic Surgeons
Climate action
Openalex Percentile: Top 20%
Lung Cancer Diagnosis and Treatment
1.52
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.