AIMC Topic: Middle Aged

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Machine learning prediction of thrombolysis efficacy using hs-CRP and inflammatory markers in stroke.

Medicine
The aim of this study was to investigate the relationship between serum ultrasensitive C-reactive protein (hs-CRP) levels and stroke incidence and to assess its potential role in decision-making for thrombolytic therapy in stroke. Given that hs-CRP i...

ZNF143 as a diagnostic biomarker: Insights from gene expression and immune cell infiltration in COPD and asthma.

Medicine
Chronic obstructive pulmonary disease (COPD) and asthma are common and serious respiratory diseases worldwide. Their clinical overlap and lack of specificity in current biomarkers pose a great diagnostic challenge for early diagnosis. To address this...

Prediction of mortality in cancer patients with COVID-19 using machine learning methods.

Medicine
This study aimed to predict mortality in cancer patients diagnosed with COVID-19 using machine learning (ML) algorithms and identify the clinical and laboratory parameters associated with mortality. Demographic, clinical, and laboratory data of cance...

AngioReport: dataset and baseline methods for fundus angiography report generation.

The British journal of ophthalmology
PURPOSE: To develop an annotated fundus angiographic dataset, including fundus fluorescein angiography (FFA) and indocyanine green angiography (ICGA), and establish baseline methods for automatic report generation.

Inherited retinal disease pathway in the UK: a patient perspective and the potential of AI.

The British journal of ophthalmology
BACKGROUND: Inherited retinal diseases (IRDs) are the leading cause of blindness in young people in the UK. Despite significant improvements in genomics medicine, the diagnosis of these conditions remains challenging, and around 40% do not receive a ...

Cardiac amyloidosis detection from a single echocardiographic video clip: a novel artificial intelligence-based screening tool.

European heart journal
BACKGROUND AND AIMS: Accurate differentiation of cardiac amyloidosis (CA) from phenotypic mimics remains challenging using current clinical and echocardiographic techniques. The accuracy of a novel artificial intelligence (AI) screening algorithm for...

Early diagnosis model of mycosis fungoides and five inflammatory skin diseases based on a multimodal data-based convolutional neural network.

The British journal of dermatology
BACKGROUND: Mycosis fungoides (MF) is the most common type of cutaneous T-cell lymphoma, and early-stage MF is difficult to differentiate from erythematous inflammatory disease. With the exception of biopsy, noninvasive information such as a patient'...

Machine Learning-Based Biomarker Identification for Early Diagnosis of Metabolic Dysfunction-Associated Steatotic Liver Disease.

The Journal of clinical endocrinology and metabolism
CONTEXT: Metabolic dysfunction-associated steatotic liver disease (MASLD) is an umbrella term for simple hepatic steatosis and the more severe metabolic dysfunction-associated steatohepatitis. The current reliance on liver biopsy for diagnosis and a ...

Machine learning-based hemodynamics quantitative assessment of pulmonary circulation using computed tomographic pulmonary angiography.

International journal of cardiology
BACKGROUND: Pulmonary hypertension (pH) is a malignant pulmonary circulation disease. Right heart catheterization (RHC) is the gold standard procedure for quantitative evaluation of pulmonary hemodynamics. Accurate and noninvasive quantitative evalua...

Inflammatory biomarkers as predictors for unlocking antidepressant efficacy: Assessing predictive value and risk stratification in major depressive disorder in a prospective longitudinal study.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) is characterized by significant heterogeneity in treatment response, with inflammation hypothesized to play a role in its pathophysiology. Peripheral inflammatory biomarkers, such as the neutrophil-to-lymph...