AIMC Topic: Middle Aged
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Turkish medical oncologists' perspectives on integrating artificial intelligence: knowledge, attitudes, and ethical considerations.
BMC medical ethics
Jul 4, 2025
BACKGROUND: Integrating artificial intelligence (AI), especially large language models (LLM) into oncology has potential benefits, yet medical oncologists' knowledge, attitudes, and ethical concerns remain unclear. Understanding these perspectives is...
Gut microbiome alterations and hepatic encephalopathy post-TIPS in liver cirrhosis patients.
Journal of translational medicine
Jul 4, 2025
BACKGROUND: The transjugular intrahepatic portosystemic shunt (TIPS), a crucial tool for treating complications related to portal hypertension in patients with liver cirrhosis, is often associated with an increased risk of postoperative complications...
Prediction of three-year all-cause mortality in patients with heart failure and atrial fibrillation using the CatBoost model.
BMC cardiovascular disorders
Jul 4, 2025
BACKGROUND: Heart failure and atrial fibrillation (HF-AF) frequently coexist, resulting in complex interactions that substantially elevate mortality risk. This study aimed to develop and validate a machine learning (ML) model predicting the 3-year al...
Humans
Boosting Machine Learning Algorithms
Female
Reproducibility of Results
Predictive Value of Tests
Risk Factors
Cause of Death
Aged
Heart Failure
Aged, 80 and over
Atrial Fibrillation
Machine Learning
Male
Decision Support Techniques
Middle Aged
Prognosis
Risk Assessment
Retrospective Studies
Time Factors
Multi-modality radiomics diagnosis of breast cancer based on MRI, ultrasound and mammography.
BMC medical imaging
Jul 4, 2025
OBJECTIVE: To develop a multi-modality machine learning-based radiomics model utilizing Magnetic Resonance Imaging (MRI), Ultrasound (US), and Mammography (MMG) for the differentiation of benign and malignant breast nodules.
Prediction of suicide using web based voice recordings analyzed by artificial intelligence.
Scientific reports
Jul 4, 2025
The integration of machine learning (ML) and deep learning models in suicide risk assessment has advanced significantly in recent years. In this study, we utilized ML in a case-control design, we predicted completed suicides using publicly available,...
A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs.
Scientific reports
Jul 4, 2025
Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are co...
Leveraging pathological markers of lower grade glioma to predict the occurrence of secondary epilepsy, a retrospective study.
Scientific reports
Jul 4, 2025
Epilepsy is a common manifestation in patients with lower grade glioma (LGG), often presenting as the initial symptom in approximately 70% of cases. This study aimed to identify clinical and pathological markers for epileptic seizures in patients wit...
5-Hydroxymethylcytosine signatures as diagnostic biomarkers for septic cardiomyopathy.
Scientific reports
Jul 4, 2025
At present, there are currently no molecular biomarkers for the early diagnosis of sepsis cardiomyopathy (SCM) in clinical practice. This study focuses on an in-depth examination of the DNA hydroxymethylation profiles within plasma extracellular vesi...
Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.
Science advances
Jul 4, 2025
Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor samples from 149 Chinese patients with breast cancer across ERHER2, ERHER2, and ERHER2 subtypes, cat...
Co-Design of a Health Screening Program Fact Sheet by People Experiencing Homelessness and ChatGPT: Focus Group Study.
JMIR formative research
Jul 4, 2025
BACKGROUND: People experiencing homelessness have worse oral health outcomes and a notable health informational asymmetry compared to the general population. Screening programs present a viable option for this population; however, barriers to access,...
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