AIMC Topic: ROC Curve
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Development of a LASSO machine learning algorithm-based model for postoperative delirium prediction in hepatectomy patients.
BMC surgery
Jan 15, 2025
OBJECTIVE: The objective of this study was to develop and validate a clinically applicable nomogram for predicting the risk of delirium following hepatectomy.
Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence.
Scientific reports
Jan 15, 2025
Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and mortality. However, the diagnostic accuracy of ultrasound, the sole prenatal screening tool, remains limited. Failed prenatal or early newborn detecti...
Artificial intelligence as a transforming factor in motility disorders-automatic detection of motility patterns in high-resolution anorectal manometry.
Scientific reports
Jan 15, 2025
High-resolution anorectal manometry (HR-ARM) is the gold standard for anorectal functional disorders' evaluation, despite being limited by its accessibility and complex data analysis. The London Protocol and Classification were developed to standardi...
Novel approach for quality control testing of medical displays using deep learning technology.
Biomedical physics & engineering express
Jan 15, 2025
In digital image diagnosis using medical displays, it is crucial to rigorously manage display devices to ensure appropriate image quality and diagnostic safety. The aim of this study was to develop a model for the efficient quality control (QC) of me...
Development of a multi-laboratory integrated predictive model for silicosis utilizing machine learning: a retrospective case-control study.
Frontiers in public health
Jan 15, 2025
OBJECTIVE: Due to the high global prevalence of silicosis and the ongoing challenges in its diagnosis, this pilot study aims to screen biomarkers from routine blood parameters and develop a multi-biomarker model for its early detection.
Using a Deep Learning Model to Predict Postoperative Visual Outcomes of Idiopathic Epiretinal Membrane Surgery.
American journal of ophthalmology
Jan 13, 2025
PURPOSE: This study assessed the performance of various deep learning models in predicting the postoperative outcomes of idiopathic epiretinal membrane (ERM) surgery based on preoperative optical coherence tomography (OCT) images.
Personalized treatment strategies for breast adenoid cystic carcinoma: A machine learning approach.
Breast (Edinburgh, Scotland)
Jan 13, 2025
BACKGROUND: Breast adenoid cystic carcinoma (BACC) is a rare subtype of breast cancer that accounts for less than 0.1 % of all cases. This study was designed to assess the efficacy of various treatment approaches for BACC and to create the first web-...
Golgi protein 73: charting new territories in diagnosing significant fibrosis in MASLD: a prospective cross-sectional study.
Frontiers in endocrinology
Jan 13, 2025
OBJECTIVES: To explore the correlation between serum Golgi protein 73 (GP73) levels and the degree of fibrosis in Metabolic dysfunction associated steatotic liver disease (MASLD); to establish a non-invasive diagnostic algorithm based on serum GP73 a...
Identification of biomarkers for knee osteoarthritis through clinical data and machine learning models.
Scientific reports
Jan 11, 2025
Knee osteoarthritis (KOA) represents a progressive degenerative disorder characterized by the gradual erosion of articular cartilage. This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning ...
Leveraging explainable AI and large-scale datasets for comprehensive classification of renal histologic types.
Scientific reports
Jan 11, 2025
Recently, as the number of cancer patients has increased, much research is being conducted for efficient treatment, including the use of artificial intelligence in genitourinary pathology. Recent research has focused largely on the classification of ...
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