AIMC Topic: Case-Control Studies
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Identification of patients at risk for pancreatic cancer in a 3-year timeframe based on machine learning algorithms.
Scientific reports
Apr 5, 2025
Early detection of pancreatic cancer (PC) remains challenging largely due to the low population incidence and few known risk factors. However, screening in at-risk populations and detection of early cancer has the potential to significantly alter sur...
Deep learning assisted retinal microvasculature assessment and cerebral small vessel disease in Fabry disease.
Orphanet journal of rare diseases
Apr 3, 2025
PURPOSE: The aim of this study was to assess retinal microvascular parameters (RMPs) in Fabry disease (FD) using deep learning, and analyze the correlation with brain lesions related to cerebral small vessel disease (CSVD).
Exploring non-invasive biomarkers for pulmonary nodule detection based on salivary microbiomics and machine learning algorithms.
Scientific reports
Mar 29, 2025
Microorganisms are one of the most promising biomarkers for cancer, and the relationship between microorganisms and lung cancer occurrence and development provides significant potential for pulmonary nodule (PN) diagnosis from a microbiological persp...
Machine learning in lymphocyte and immune biomarker analysis for childhood thyroid diseases in China.
BMC pediatrics
Mar 28, 2025
OBJECTIVE: This study aims to characterize and analyze the expression of representative biomarkers like lymphocytes and immune subsets in children with thyroid disorders. It also intends to develop and evaluate a machine learning model to predict if ...
Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning.
PloS one
Mar 25, 2025
BACKGROUND: Systemic lupus erythematosus (SLE) is a complex autoimmune disease that has significant impacts on patients' quality of life and poses a substantial economic burden on society.
Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Mar 23, 2025
Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly sensitive and minimally invasive early diagnostic methods. Near-infrared spectroscopy (NIRS) offers unique advantages in probing molecular vibrational i...
Enhancing diagnostic accuracy for HBV-related cirrhosis progression: predictive modeling using combined Golgi protein 73 and α1-microglobulin for the transition from nondecompensated to decompensated cirrhosis.
European journal of gastroenterology & hepatology
Mar 21, 2025
BACKGROUND AND AIMS: Chronic hepatitis B poses a major health risk, especially its progression to decompensated cirrhosis. Early prediction is crucial for better outcomes. This study evaluated the predictive power of Golgi protein 73 (GP73), α1-micro...
Hepatitis B, Chronic
Middle Aged
Membrane Proteins
Humans
Platelet Count
Disease Progression
Female
Age Factors
Alanine Transaminase
Case-Control Studies
Machine Learning
Aged
Decision Trees
Aspartate Aminotransferases
Logistic Models
Biomarkers
Adult
Predictive Value of Tests
Alpha-Globulins
Liver Cirrhosis
Male
A diagnostic model for polycystic ovary syndrome based on machine learning.
Scientific reports
Mar 21, 2025
Diagnosis of polycystic ovary syndrome remains a challenge. In this study, we propose constructing a diagnostic model of polycystic ovary syndrome by combining anti-Müllerian hormone with steroid hormones and oestrogens, with the aim of providing mor...
Exploring the role of breastfeeding, antibiotics, and indoor environments in preschool children atopic dermatitis through machine learning and hygiene hypothesis.
Scientific reports
Mar 21, 2025
The increasing global incidence of atopic dermatitis (AD) in children, especially in Western industrialized nations, has attracted considerable attention. The hygiene hypothesis, which posits that early pathogen exposure is crucial for immune system ...
Rapid, non-invasive breath analysis for enhancing detection of silicosis using mass spectrometry and interpretable machine learning.
Journal of breath research
Mar 21, 2025
Occupational lung diseases, such as silicosis, are a significant global health concern, especially with increasing exposure to engineered stone dust. Early detection of silicosis is helpful for preventing disease progression, but existing diagnostic ...
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