AIMC Topic: Female

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Sex-specific prognostic value of automated epicardial adipose tissue quantification on serial lung cancer screening chest computed tomography.

European heart journal. Cardiovascular Imaging
AIMS: Epicardial adipose tissue (EAT) is a metabolically active fat depot associated with coronary atherosclerosis and cardiovascular (CV) risk. While EAT is a known prognostic marker in lung cancer screening, its sex-specific prognostic value remain...

Foam sclerotherapy for symptomatic cysts in ADPKD, ADPLD and solitary cysts.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: This medical center migrated from alcohol to sotradecol foam sclerotherapy (SFS) because of perceived improved efficacy in managing symptomatic kidney and liver cysts. We report technical aspects, change in short- and long-term cyst volum...

Monitoring ctDNA in aggressive B-cell lymphoma: a prospective correlative study of ctDNA kinetics and PET-CT metrics.

Blood advances
Positron emission tomography-computed tomography (PET-CT) is recommended for response evaluation in aggressive large B-cell lymphoma (LBCL) but cannot detect minimal residual disease (MRD). Circulating tumor DNA (ctDNA) has emerged as a promising bio...

Artificial Intelligence for Assessment of Digital Mammography Positioning Reveals Persistent Challenges.

Journal of breast imaging
OBJECTIVE: Mammographic breast cancer detection depends on high-quality positioning, which is traditionally assessed and monitored subjectively. This study used artificial intelligence (AI) to evaluate mammography positioning on digital screening mam...

Robustness of steroidomics-based machine learning for diagnosis of primary aldosteronism: a laboratory medicine perspective.

Clinical chemistry and laboratory medicine
OBJECTIVES: Use of machine learning (ML) in diagnostics offers promise to optimise interpretation of laboratory data and guide clinical decision-making. For this, ML-based outputs should provide robustly reproducible results at least as good as the u...

Machine learning reveal shared diagnostic biomarkers and convergent pathways in age-related hearing loss and sarcopenia.

Medicine
Age-related hearing loss (HL) and sarcopenia (ARS) are prevalent geriatric syndromes sharing common risk factors. This study aimed to identify shared biomarkers and elucidate convergent pathogenic mechanisms. Transcriptomic datasets were obtained fro...

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...

Integrated bioinformatics analysis and machine learning identifies FZD4, SRPX2, and COL8A1 as angiogenesis hub genes in endometriosis.

Medicine
This study aims to identify angiogenesis-associated genes (AAGs) in endometriosis (EM) by integrating bioinformatics analysis with machine learning, and to investigate their underlying mechanisms. Differentially expressed genes (DEGs) were screened f...

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...