AIMC Topic: Middle Aged

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Surface proteome of plasma extracellular vesicles differentiates between SARS-CoV-2 and influenza infection.

Virulence
Small extracellular vesicles (sEVs) play a role in the pathophysiology of viral respiratory infections and may be suitable biomarkers for COVID-19 and Influenza infections, or targets for treatment. We investigated differences in the surface proteome...

MRI quantitative imaging biomarkers in differentiating brain parenchymal tuberculoma and lung cancer brain metastases.

European journal of medical research
BACKGROUND: Brain parenchymal tuberculoma (BT) and brain metastases (BM) originating from lung cancer often exhibit overlapping clinical and imaging features, making accurate differentiation challenging. Current diagnostic approaches remain suboptima...

Association of albumin-bilirubin grade with prognosis in ICU patients with pulmonary edema: a retrospective cohort study and a predictive model based on machine learning.

BMC pulmonary medicine
BACKGROUND: The Albumin-Bilirubin (ALBI) grade was initially used to assess liver reserve function in patients with cirrhosis and has since been applied in the prognostic evaluation of various diseases. This study explored the relationship between th...

LAC-TME classifier: machine learning-driven model predicts survival and prioritizes targeted therapy in clear cell renal cell carcinoma.

Journal of cancer research and clinical oncology
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a major type of kidney cancer, making up about 80% of cases, with advanced stages showing low survival rates. Current treatments face challenges like toxicity and drug resistance. Studies indicat...

Garden classification of femoral neck fracture using deep-learning algorithm.

Scientific reports
The Garden classification, based on X-ray interpretation and established over 50 years ago, remains the standard clinical classification system for femoral neck fractures (FNFs). Yet, this classification has a high interobserver variability of 70%. W...

Comparing psychedelic and meditation experience reports with natural language processing.

Scientific reports
Psychedelics and meditation are known for their potential to induce personally meaningful and even transformative experiences. However, it is unclear how similar these experiences are, or how they differ from each other. This explorative study used n...

Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma.

Scientific reports
Glioblastoma is characterized by diffuse infiltration, making accurate detection of residual disease essential for improving prognostication and guiding treatment. This study evaluates whether the volume of predicted infiltration, generated by a mach...

Development and validation of a machine learning model to predict moderate-to-severe cancer-related fatigue in breast cancer.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aimed to establish and validate a machine learning model for predicting moderate-to-severe cancer-related fatigue (CRF) 2 years after completion of anti-tumor therapy in breast cancer patients.

Predicting and explaining life satisfaction among older adults using tree-based ensemble models and SHAP: Evidence from the digital divide survey.

PloS one
As digital transformation continues to penetrate various sectors of society, the issue of the digital divide has become increasingly prominent. Against the backdrop of accelerating population aging, the barriers that older adults face in accessing an...

Machine learning-based mortality risk prediction model for elderly diabetic patients with non-ST-segment elevation myocardial infarction using MIMIC-IV database.

Scientific reports
Non-ST-elevation myocardial infarction (NSTEMI) in elderly diabetic patients presents unique challenges in risk assessment and prognosis prediction. This study aimed to develop and validate a machine learning-based mortality risk prediction model for...