AIMC Topic: Retrospective Studies

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Development and validation of a machine learning-based predictive model for clinical remission in Crohn's disease patients receiving Adalimumab therapy.

PloS one
Crohn's disease (CD), a chronic inflammatory bowel disease, is witnessing a rising global incidence. Adalimumab (ADA), a biological agent, is widely used in its treatment. However, patients exhibit significant individual variability in responses to A...

Development and validation of an explainable machine learning model for predicting sepsis risk following flexible ureteroscopic lithotripsy.

Urolithiasis
Sepsis is a severe complication of flexible ureteroscopic lithotripsy (fURL), a widely used treatment for kidney stones. This study aimed to develop and validate a predictive model based on machine learning (ML) for assessing the risk of sepsis follo...

Predicting severe renal dysfunction in alcohol-associated cirrhosis: Comparative performance of liver function scores and machine learning models.

PloS one
BACKGROUND: Renal dysfunction is a frequent and clinically relevant complication of cirrhosis, yet chronic kidney disease (CKD) often remains underrecognized, particularly in non-acute settings. Early identification of at-risk patients is essential t...

Interpretable Machine Learning for Predicting Adverse Pregnancy Outcomes in Gestational Diabetes: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Gestational diabetes mellitus (GDM) affects over 5% of pregnancies worldwide, elevating risks of type 2 diabetes post partum and complications such as fetal death, miscarriage, and congenital abnormalities. Effective GDM management is ess...

Development of a Data-Based Method for Predicting Nursing Workload in an Acute Care Hospital: Methodological Study.

Journal of medical Internet research
BACKGROUND: Determining effective nurse staffing levels is crucial for ensuring quality patient care and operational efficiency within hospitals. Traditional workload prediction methods often rely on professional judgment or simple volume-based appro...

Real-Time Estimation of Arterial Partial Pressure of Carbon Dioxide in Patients Undergoing General Anesthesia: Predictive Modeling Study.

JMIR medical informatics
BACKGROUND: Adequate ventilation in mechanically ventilated patients is contingent upon the monitoring of the arterial partial pressure of carbon dioxide (PaCO2) during general anesthesia. Despite its significance, continuous monitoring remains chall...

Development of a predictive model for distant metastasis in HCC patients post-TACE using clinical data, radiomics, and deep learning.

Journal of cancer research and clinical oncology
PURPOSE: Hepatocellular carcinoma (HCC) is a perilous malignant tumor, and transcatheter arterial chemoembolization (TACE) is a widely adopted treatment technique for advanced HCC. Nevertheless, TACE may not effectively reduce the risk of distant met...

Clinical parameters-based machine learning models for predicting intraoperative hemodynamic instability in hypertensive pheochromocytomas and paragangliomas patients.

World journal of urology
PURPOSE: To create machine learning (ML) models based on inflammatory markers and coagulation parameters for predicting intraoperative hemodynamic Instability (HI) in sustained hypertensive patients with pheochromocytomas and paragangliomas (PPGLs).

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...

Immune-enhanced machine learning approach for early detection of precancerous colorectal neoplasia: Insights from biomarkers in routine health checkups.

European journal of cancer (Oxford, England : 1990)
BACKGROUND AND AIMS: Current screening strategies for colorectal cancer (CRC) rely on colonoscopy, an invasive procedure with limited capacity to address individual risk. There is growing interest in integrating noninvasive immune biomarkers to impro...