AIMC Topic: Middle Aged

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Interpretable Machine Learning Model for Predicting and Assessing the Risk of Diabetic Nephropathy: Prediction Model Study.

JMIR medical informatics
BACKGROUND: Diabetic nephropathy (DN), a severe complication of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal disease. The International Diabetes Federation pro...

Development and Validation of an Extra Spindle Pole Bodies-like 1-Based Diagnostic and Prognostic Model for Hepatitis B Virus-Related Hepatocellular Carcinoma: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Early diagnosis of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B virus (HBV) is challenging. Models that combine novel biomarkers with clinical features may improve both early diagnosis and risk stratification, but f...

Automated AI detection of thoracic aortic dissection on CT imaging.

European radiology experimental
BACKGROUND: Aortic dissection (AD) is a life-threatening condition. We developed an artificial intelligence (AI) algorithm capable of robust, accurate, and automated AD detection and sub-classification.

Gaining Brain Insights by Tapping into the Black Box: Linking Structural MRI Features to Age and Cognition using Shapley-Based Interpretation Methods.

Neuroinformatics
Global interpretability in machine learning holds great potential for extracting meaningful insights from neuroimaging data to improve our understanding of brain function. Although various approaches exist to identify key contributing features at bot...

Bidirectional analysis of seizure patterns and menstrual cycle phases extracted from physiological signals.

Physiological measurement
. This exploratory study investigates cyclical changes in physiological features across the menstrual cycle in women with epilepsy, focusing on their potential relationship with seizure occurrence.. Nocturnal data during sleep were collected from two...

A machine learning approach for predicting 72-hour mortality of hypothermic patients only using non-invasive parameters: A multi-center retrospective cohort study.

PloS one
OBJECTIVES: Accurately predicting the mortality risk of hypothermia patients is crucial for clinical decision-making, offering ample time for physicians to intervene. However, existing methods are invasive and difficult to implement in pre-hospital s...

Effects of iron repletion on brain iron content, myelination, neural network activation, and cognition.

JCI insight
BACKGROUNDBlood donation increases the risk of iron deficiency, but its effect on brain iron, myelination, and neurocognition remains unclear.METHODSThis ancillary study enrolled 67 iron-deficient blood donors, 19-73 years of age, participating in a ...

Aging as an active player in Alzheimer's disease classification: Insights from feature selection in BrainAge models.

NeuroImage
BACKGROUND: BrainAge models estimate the biological age of the brain using neuroimaging or clinical features, making them promising tools for studying neurodegenerative diseases like Alzheimer's disease. However, the reliance of BrainAge models on ne...

DEHP promotes psoriasis via immune modulation and direct molecular interactions: Evidence from epidemiology, multi-omics, and structural simulation.

The Science of the total environment
Di (2-ethylhexyl) phthalate (DEHP), a widely used plasticizer with known immunotoxic effects, has been suspected of aggravating inflammatory skin conditions, yet its role in autoimmune diseases such as psoriasis remains poorly defined. In this study,...