AIMC Topic: Middle Aged

Clear Filters Showing 51 to 60 of 17155 articles

Long-term benefit from high-dose ifosfamide in sarcoma depends on sustained prior control and timely intervention: a machine learning analysis.

Journal of cancer research and clinical oncology
PURPOSE: High-dose ifosfamide (HD-IFO) remains an effective regimen for advanced bone and soft tissue sarcomas, but predictors of long-term benefit are poorly defined. This study evaluated clinical outcomes and prognostic factors using machine learni...

A pretrained foundation model for headache disorders based on magnetoencephalography.

Journal of neural engineering
Foundation models have demonstrated transformative potential in medical artificial intelligence but remain underexplored in functional neuroimaging, particularly magnetoencephalography (MEG). This study aims to develop a domain-specific, self-supervi...

Machine learning-based cardiovascular risk calculator for non-cardiac surgery.

Open heart
BACKGROUND: Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least one cardiovascular risk factor. It is estimated that the 30-day mortality is between 0.5% and 2%.The main objective of this st...

Clinical testing of drug treatment shortening in patients with TB using PET/CT imaging of lung lesions.

Science translational medicine
Six months of drug treatment is standard of care for drug-sensitive pulmonary tuberculosis (TB). Understanding the factors determining the length of treatment required for durable cure would allow individualization of treatment durations. We conducte...

Large Language Models in Patient Health Communication for Atherosclerotic Cardiovascular Disease: Pilot Cross-Sectional Comparative Analysis.

JMIR medical informatics
BACKGROUND: Large language models (LLMs) have emerged as promising tools for enhancing public access to medical information, particularly for chronic diseases such as atherosclerotic cardiovascular disease (ASCVD). However, their effectiveness in pat...

Deep Learning for Dynamic Prognostic Prediction in Minimally Invasive Surgery for Intracerebral Hemorrhage: Model Development and Validation Study.

JMIR medical informatics
BACKGROUND: The pathological and physiological state of patients with intracerebral hemorrhage (ICH) after minimally invasive surgery (MIS) is a dynamic evolution, and the traditional models cannot dynamically predict prognosis. Clinical data at mult...

Unbiased inference for echocardiogram urgency prediction using double machine learning.

PloS one
The increased utilization of echocardiography in clinical practice has witnessed a substantial rise, underscoring its pivotal role as a diagnostic tool for various cardiovascular conditions. However, due to the relative scarcity of echocardiography t...

Diagnostic performance of eNose technology in detecting colorectal cancer recurrence: A prospective evaluation.

PloS one
INTRODUCTION: After curative treatment for colorectal cancer (CRC), there is a 15% risk of recurrence. Early detection of an asymptomatic recurrence may lead to curative treatment options. To date, follow-up strategies do not have optimal sensitivity...

Personalized Machine Learning Intervention to Improve Sleep Quality Using Wearable Technology in Healthy Middle-Aged Adults From Mexico City: Protocol for a Pilot Randomized Controlled Trial.

JMIR research protocols
BACKGROUND: In 2019, global sleep surveys reported that 80% of adults want to improve their sleep quality, and in 2021, 45% were reported to be dissatisfied with their sleep. In 2025, among American adults, 37% reported sleep dissatisfaction and 38% ...

PRIME: an interpretable artificial intelligence model based on liquid biopsy improves prediction of progression risk in non-small cell lung cancer.

Military Medical Research
BACKGROUND: Despite the predictive impact of circulating tumor DNA (ctDNA) minimal residual disease (MRD), accurate prediction of failure risk after curative-intent treatments for early-stage or localized non-small cell lung cancer (NSCLC) patients t...