AIMC Topic: Aged

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Integrating deep learning and radiomics for preoperative glioma grading using multi-center MRI data.

Scientific reports
Accurate preoperative glioma grading remains a critical challenge in neuro-oncology. This study presents a novel integrated approach combining deep learning architectures with radiomics features derived from multi-parametric MRI to improve preoperati...

Exploring the therapeutic effects of continuous kidney replacement therapy in patients with severe acidosis using deep learning-based causal inference.

Scientific reports
Continuous kidney replacement therapy (CKRT) is an essential treatment for uncontrolled severe metabolic acidosis. However, CKRT can increase workload and lead to complications, thus necessitating its selective application to patients who stand to be...

3D deep learning-based muscle volume quantification from thoracic CT as a surrogate for DXA-Derived appendicular muscle mass in older adults.

Aging clinical and experimental research
BACKGROUND: In order to identify patients with sarcopenia, the use of routine imaging could provide valuable support. One of the most common radiological examinations, especially in geriatric inpatient care, is CT thoracic imaging. Therefore, it woul...

Evaluation of inflammatory markers in survival analysis of patients undergoing radical cystectomy using machine learning.

World journal of urology
BACKGROUND: We aimed to create a Machine learning (ML) model using patient demographic, clinical and pathological data for prediction of overall survival in patients treated with radical cystectomy (RC). Secondly, we evaluated whether inflammatory ma...

Prognostic value of admission ROTEM in trauma: enhancing 30-day all-cause mortality prediction using machine learning.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
BACKGROUND: Haemorrhage is a leading cause of trauma death, yet early coagulation markers are rarely used to predict long-term outcomes. This study assessed whether a single admission rotational thromboelastometry (ROTEM) test could independently pre...

Machine learning-enhanced normal tissue complication probability modeling for late sciatic nerve toxicity prediction in carbon-ion radiotherapy: model development and clinical validation.

Physics in medicine and biology
To develop a machine learning-enhanced normal tissue complication probability (NTCP) model for predicting late sciatic nerve toxicity (LSNT) in sacrococcygeal chordoma (SC) and locally recurrent rectal cancer (LRRC) patients undergoing carbon-ion rad...

Development and validation of a bedside-available machine learning model to predict discrepancies between SaO₂ and SpO₂: Exploring factors related to the discrepancies.

PloS one
In critically ill patients, a discrepancy frequently exists between percutaneous oxygen saturation (SpO₂) and arterial blood oxygen saturation (SaO₂), which can lead to potential hypoxemia being overlooked. The aim of this study was to explore the fa...

Subvisual imaging signals as biomarkers of impending lung metastasis: A multicenter pan-cancer study.

European journal of cancer (Oxford, England : 1990)
STUDY AIM: Early detection of distant metastases is crucial, but current imaging detects them only when radiographically visible. This study reported subvisual chest CT signals could serve as early biomarkers for impending lung metastasis before radi...

Cardiovascular risk assessment enhanced by automated machine learning in a multi-phase study.

Scientific reports
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and current predictors such as lipoprotein (a) [Lp(a)] and risk scores have limitations. Automated machine learning (AutoML) offers the potential to improve CVD risk prediction ...

A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region.

Scientific reports
Improving accuracy and timeliness for osteoporosis diagnosis could help prevent fragility fractures, morbidity, and mortality for older individuals. Osteoporosis is an often silent health condition, especially as regards vertebral fractures, and WHO ...