AIMC Topic: Case-Control Studies
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Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening.
BMC pregnancy and childbirth
Apr 14, 2025
BACKGROUND: Circulating cell-free RNA (cfRNA) is gaining recognition as an effective biomarker for the early detection of preeclampsia (PE). However, the current methods for selecting disease-specific biomarkers are often inefficient and typically on...
Unique and shared transcriptomic signatures underlying localized scleroderma pathogenesis identified using interpretable machine learning.
JCI insight
Apr 8, 2025
Using transcriptomic profiling at single-cell resolution, we investigated cell-intrinsic and cell-extrinsic signatures associated with pathogenesis and inflammation-driven fibrosis in both adult and pediatric patients with localized scleroderma (LS)....
Structural brain pattern abnormalities in tinnitus with and without hearing loss.
Hearing research
Apr 6, 2025
OBJECTIVE: Subjective tinnitus often coexists with hearing loss, and they share common pathophysiological mechanisms. This comorbidity induces whole-brain gray matter volume (GMV) alterations, manifesting as distributed structural changes in neural n...
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...
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...
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