AIMC Topic: Case-Control Studies

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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
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...

Alternations of Gut Microbiome and Serum Metabolome With Prolongation of the Course of Type 1 Diabetes Mellitus.

Diabetes/metabolism research and reviews
AIMS: We aimed to explore the gut microbial and serum metabolic disturbances associated with the course of type 1 diabetes mellitus (T1DM), and identify potential biomarkers for discriminating T1DM from normoglycemia individuals by machine learning.

Utilizing Artificial Intelligence: Machine Learning Algorithms to Develop a Preoperative Endometriosis Prediction Model.

Journal of minimally invasive gynecology
OBJECTIVE: To evaluate the predictive value of clinical features in the diagnosis of endometriosis by utilizing machine learning algorithms (MLAs), aiming to develop an accurate, explainable prediction model.

The association between maternal exposure to ten neonicotinoid insecticides and preterm birth in Guangxi, China.

Environmental pollution (Barking, Essex : 1987)
Preterm birth (PTB) is a primary cause of mortality among newborns globally. Prenatal exposure to environmental pollutants has been suggested to increase the PTB risk. Studies have shown NEOs may be linked to adverse birth outcomes. However, the impa...

Algorithmic Fairness in Machine Learning Prediction of Autism Using Electronic Health Records.

Studies in health technology and informatics
Efforts to improve early diagnosis of autism spectrum disorder (ASD) in children are beginning to use machine learning (ML) approaches applied to real-world clinical datasets, such as electronic health records (EHRs). However, sex-based disparities i...

Effect of Deep Learning-Based Artificial Intelligence on Radiologists' Performance in Identifying Nigrosome 1 Abnormalities on Susceptibility Map-Weighted Imaging.

Korean journal of radiology
OBJECTIVE: To evaluate the effect of deep learning (DL)-based artificial intelligence (AI) software on the diagnostic performance of radiologists with different experience levels in detecting nigrosome 1 (N1) abnormalities on susceptibility map-weigh...

Circulating Proteomic Panels for Noninvasive Diagnosis and Prognostication of Thromboangiitis Obliterans.

Journal of proteome research
Thromboangiitis obliterans (TAO) is often diagnosed late and characterized by high amputation rates. TAO-specific early diagnostic and disease-staging biomarkers are urgently needed. A staged mass spectrometry (MS)-based discovery-verification-valida...

Integrative exome sequencing and machine learning identify MICB and interferon pathway genes as contributors to SSc risk.

Annals of the rheumatic diseases
OBJECTIVES: Systemic sclerosis (SSc) is a complex autoimmune disease with both known and unidentified genetic contributors. While genome-wide association studies (GWAS) have implicated multiple loci, many reside in noncoding regions. We aimed to iden...

Infrared and Raman spectroscopy of blood plasma for rapid endometrial cancer detection.

British journal of cancer
BACKGROUND: Endometrial cancer (EC) is the 6th most common cancer among women worldwide. No effective non-invasive screening methods or approved blood biomarkers for EC exist. Previous research explored Attenuated Total Reflection-Fourier Transform I...

Detection of Early-Stage Colorectal Cancer Using Cell-Free oncRNA Biomarkers and Artificial Intelligence.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Colorectal cancer is the second leading cause of cancer-related deaths worldwide, and early detection significantly improves treatment outcomes, but existing blood-based tests often have limited sensitivity in early-stage disease. We develop...