AIMC Topic: Propensity Score

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Primary tumor resection: a new hope or an old illusion for patients with metastatic non-small cell lung neuroendocrine tumors?

World journal of surgical oncology
OBJECTIVES: This study aimed to investigate the impact of primary tumor resection (PTR) on survival outcomes for patients with metastatic non-small cell neuroendocrine tumors (mNSCLC-NETs), develop a predictive model to identify which patients may be...

Association between atherogenic index of plasma and sepsis in critically ill patients with ischemic stroke: a retrospective cohort study using propensity score and machine learning approaches.

Lipids in health and disease
BACKGROUND: Sepsis is a severe and frequent complication among ischemic stroke patients during hospitalization. The atherogenic index of plasma (AIP), as metabolism-related markers, are closely linked to inflammation. However, their relationship with...

Association between geriatric nutritional risk index (GNRI) and asthma in elderly individuals aged 60 and above: a cross-sectional study of the NHANES 2005-2018.

BMC pulmonary medicine
OBJECTIVE: The geriatric nutritional risk index (GNRI) is a promising tool for predicting nutrition-related complications in older adults. This study aimed to explore the association between GNRI and asthma in individuals aged 60 and above.

Genetic algorithm-optimized neural network outperforms TNM staging in predicting rapidly progressive nasopharyngeal carcinoma: Reassessing adjuvant chemotherapy benefit via propensity score matching.

European journal of cancer (Oxford, England : 1990)
PURPOSE: To establish machine learning-based predictive models for rapidly progressive nasopharyngeal carcinoma (RP-NPC), defined as disease progression within 24 months post-initial treatment, and to assess differential survival benefits of adjuvant...

Survival impact of adjuvant radiotherapy in early stage low risk elderly male breast cancer patients treated with breast conserving surgery.

Scientific reports
Our study aimed to evaluate the survival impact of adjuvant radiotherapy (RT) following breast-conserving surgery (BCS) in elderly male patients with early-stage, low-risk breast cancer (node-negative, HR+), and to identify RT-benefiting subgroups us...

A retrospective cohort study using machine learning to predict coronary artery lesions in children with Kawasaki disease.

BMC pediatrics
BACKGROUND: Kawasaki disease (KD) mainly occurs in children under 5 years old, and the most common complication of KD is coronary artery lesion (CAL). In recent years, the incidence rate of KD has increased year by year worldwide, so it is particular...

Machine learning-based high-benefit approach versus traditional high-risk approach in statin therapy: the Shizuoka Kokuho database study.

Scientific reports
Statins are widely prescribed for the primary prevention of cardiovascular diseases, yet individual responses vary, necessitating personalized treatment strategies. Conventional approaches prioritize treating high-risk patients, but advancements in m...

Using Machine Learning to Match Clients and Therapy Providers: Evaluating Clinical Quality and Cost of Care.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Matching clients in need of mental healthcare with providers who will deliver high quality treatment presents a substantial challenge. Machine learning models hold potential for predicting the best pairings from a multitude of data points...

Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.

Scientific reports
Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative, or missingness) in binary categorical variables in electronic medical records (EMRs) using propens...