Machine learning prediction of postoperative pulmonary infection in patients who underwent thoracoscopic lung cancer resection: a retrospective case-control study.
BACKGROUND: Accurate identification of patients at high risk of pulmonary infection after thoracoscopic lung cancer resection is important for timely and targeted preventive measures. RESULTS: There were 3219 enrolled patients, 2203 (70%) of whom were assigned to the training cohort and 966 (30%) of whom were assigned to the validation cohort.
BACKGROUND: Accurate identification of patients at high risk of pulmonary infection after thoracoscopic lung cancer resection is important for timely and targeted preventive measures. RESULTS: There were 3219 enrolled patients, 2203 (70%) of whom were assigned to the training cohort and 966 (30%) of whom were assigned to the validation cohort.
What the study was
- Study design
- Cohort study
- Category
- Other
- Maturity
- Exploratory
- Journal
- BMC medical informatics and decision making
Why it surfaced
Relevant Sentinel scan study (promising preliminary signal) meets standard-priority threshold.
A plain-language summary of published research — not medical advice. Talk to a clinician about your own care.