AIMC Topic: ROC Curve

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Machine learning approaches for predicting heart failure readmissions.

Postgraduate medical journal
PURPOSE: This study aims to develop and evaluate machine learning (ML) models to predict the likelihood of hospital readmission within 30 days after discharge for patients with heart failure (HF). The goal is to compare the predictive accuracy of ML ...

Prognostic factors and prediction model for facial scar improvement in laser-treated patients: A machine learning-based retrospective cohort study.

Medicine
The face, being central and exposed, is highly susceptible to trauma and subsequent scar formation. Laser therapy is a common and effective treatment method for facial scars. However, treatment outcomes vary substantially. Consequently, we aimed to i...

Machine learning-based screening of characteristic factors for urinary tract infection following ureteral stone surgery and construction and validation of risk prediction models.

Medicine
Ureteroscopic lithotripsy has emerged as the cornerstone treatment modality for ureteral stones due to its exceptional success rates and minimal complication profiles. Nevertheless, postoperative urinary tract infection (UTI) remains a prevalent and ...

Predicting Urine Culture Outcomes in Adult Patients Using Machine Learning with the Aim of Reducing Unnecessary Urine Cultures.

The journal of applied laboratory medicine
BACKGROUND: Urine cultures are frequently ordered tests with a low positivity rate. Development of a machine learning model to predict urine culture outcomes could not only reduce unnecessary urine cultures but also prevent preliminary antibiotic tre...

Dynamic machine learning models for predicting cesarean delivery risk in women with no prior cesarean delivery: A retrospective nationwide cohort analysis.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To develop and validate advanced machine learning (ML) models for predicting unplanned intrapartum cesarean deliveries in women with no previous cesarean delivery, using both static and dynamic clinical data.

Machine learning reveal shared diagnostic biomarkers and convergent pathways in age-related hearing loss and sarcopenia.

Medicine
Age-related hearing loss (HL) and sarcopenia (ARS) are prevalent geriatric syndromes sharing common risk factors. This study aimed to identify shared biomarkers and elucidate convergent pathogenic mechanisms. Transcriptomic datasets were obtained fro...

Machine learning prediction of thrombolysis efficacy using hs-CRP and inflammatory markers in stroke.

Medicine
The aim of this study was to investigate the relationship between serum ultrasensitive C-reactive protein (hs-CRP) levels and stroke incidence and to assess its potential role in decision-making for thrombolytic therapy in stroke. Given that hs-CRP i...

ZNF143 as a diagnostic biomarker: Insights from gene expression and immune cell infiltration in COPD and asthma.

Medicine
Chronic obstructive pulmonary disease (COPD) and asthma are common and serious respiratory diseases worldwide. Their clinical overlap and lack of specificity in current biomarkers pose a great diagnostic challenge for early diagnosis. To address this...

Machine Learning-based Prediction of Active Tuberculosis in People With HIV Using Clinical Data.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
BACKGROUND: Coinfections of Mycobacterium tuberculosis (MTB) and human immunodeficiency virus (HIV) impose a substantial global health burden. Patients with MTB infection face a heightened risk of progression to incident active TB, which preventive t...

Artificial Intelligence-Based Classification of Renal Oncocytic Neoplasms: Advancing From a 2-Class Model of Renal Oncocytoma and Low-Grade Oncocytic Tumor to a 3-Class Model Including Chromophobe Renal Cell Carcinoma.

Archives of pathology & laboratory medicine
CONTEXT.—: Distinguishing between renal oncocytic tumors, such as renal oncocytoma (RO), and a subset of tumors with overlapping characteristics, including the recently identified low-grade oncocytic tumor (LOT), can present a diagnostic challenge fo...