AIMC Topic: Logistic Models
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Development of a single-center predictive model for conventional in vitro fertilization outcomes excluding total fertilization failure: implications for protocol selection.
Journal of ovarian research
Jul 2, 2025
OBJECTIVES: To develop a multidimensional clinical indicator-based prediction model for identifying high-risk patients with fertilization failure conventional in vitro fertilization (c-IVF) cycles, thereby optimizing therapeutic decision-making.
Prediction of caesarean section birth using machine learning algorithms among pregnant women in a district hospital in Ghana.
BMC pregnancy and childbirth
Jul 2, 2025
BACKGROUND: Machine learning algorithms may contribute to improving maternal and child health, including determining the suitability of caesarean section (CS) births in low-resource countries. Despite machine learning algorithms offering a more robus...
Key factors in predictive analysis of cardiovascular risks in public health.
Scientific reports
Jul 2, 2025
This research emphasizes the role of analytics in evaluating the risk of disease (CVD) focusing on thorough data preparation and feature engineering for accurate predictions. We studied machine learning (ML) and learning (DL) models, such as Logistic...
Machine learning to improve predictive performance of prehospital early warning scores.
Scientific reports
Jul 1, 2025
Early warning scores are used to assess acute patients' risk of being in a critical situation, allowing for early appropriate treatment, avoiding critical outcomes. The early warning scores use changes in vital signs to provide an assessment, however...
Prediction of cardiovascular diseases based on GBDT+LR.
Scientific reports
Jul 1, 2025
Currently, there are over 300 million patients with cardiovascular diseases in China. With the acceleration of population aging, the impact of cardiovascular diseases is becoming increasingly severe. Accurately and efficiently predicting the potentia...
Establishment of a machine learning-based predictive model with dual-center external validation: investigating the role of robotic surgery in preventing delayed gastric emptying for right-sided colon cancer.
Journal of robotic surgery
Jun 30, 2025
After colorectal surgery, delayed gastric emptying (DGE) is a clinically significant postoperative complication that significantly lowers patients' quality of life. The evolving application of robotic surgery in gastrointestinal oncology continues to...
Machine learning model for the prediction of postoperative acute kidney injury (AKI) in neonates undergoing digestive surgery.
Pediatric surgery international
Jun 24, 2025
OBJECTIVE: The aim of our study is to determine the main predictors of postoperative AKI in neonates using machine learning models compared with the logistic regression model.
Exploring the association between volatile organic compound exposure and chronic kidney disease: evidence from explainable machine learning methods.
Renal failure
Jun 23, 2025
BACKGROUND: Chronic Kidney Disease (CKD) affects approximately 697.5 million people worldwide. Volatile organic compounds (VOCs) are emerging as potential risk factors, but their complex relationships with CKD may be underestimated by traditional lin...
The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.
The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
Jun 23, 2025
: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolitis (NEC). Thus, establishing a novel and simple prediction model is of great clinical significance. ...
Prediction of future aging-related slow gait and its determinants with deep learning and logistic regression.
PloS one
Jun 17, 2025
BACKGROUND: Identification of accelerated aging and its biomarkers can lead to more timely therapeutic interventions and decision-making. Therefore, we sought to predict aging-related slow gait, a known predictor of accelerated aging, and its determi...
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