AIMC Topic: Aged

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An interpretable machine learning model based on MRI radiomics and GAME score for predicting early recurrence after thermal ablation in colorectal liver metastases.

International journal of colorectal disease
OBJECTIVE: To develop and validate machine learning models based on preoperative magnetic resonance imaging(MRI) and baseline clinical characteristics for predicting early recurrence(ER) in patients with colorectal liver metastases(CRLM) treated with...

Early Prediction of Cardiac Arrest Based on Time-Series Vital Signs Using Deep Learning: Retrospective Study.

JMIR formative research
BACKGROUND: Cardiac arrest (CA), characterized by an extremely high mortality rate, remains one of the most pressing global public health challenges. It not only causes a substantial strain on health care systems but also severely impacts individual ...

Physical Activity Recommendations Tailored by a Predictive Model for Adults With High Blood Pressure: Observational Study.

Journal of medical Internet research
BACKGROUND: Whether the benefits of identical physical activity (PA) patterns for adults with high blood pressure (BP) vary according to an individual's characteristics has not been adequately studied.

Selective classification with machine learning uncertainty estimates improves ACS prediction: a retrospective study in the prehospital setting.

Scientific reports
Accurate identification of acute coronary syndrome (ACS) in the prehospital setting is important for timely treatments that reduce damage to the compromised myocardium. Current machine learning approaches lack sufficient performance to safely rule-in...

AI-enabled electrocardiogram alert for potassium imbalance treatment: a pragmatic randomized controlled trial.

Nature communications
Life-threatening dyskalemia, defined as an abnormal serum potassium concentration, is common in emergency settings that requires timely recognition and treatment and can be detected via AI-enabled electrocardiography. We conducted a pragmatic, open-l...

Sex-specific machine learning models for carotid plaque prediction in individuals with fatty liver disease: a cross-sectional study.

BMJ open
INTRODUCTION: Early detection of carotid plaque prevents stroke and myocardial infarction. Individuals with fatty liver might be at an increased risk of developing carotid plaque, yet limited access to carotid artery ultrasound underscores the need f...

Assessment of Blood Glucose Measurement Using New Noninvasive Technology: Protocol and Methodology.

JMIR research protocols
BACKGROUND: Diabetes mellitus (DM) is a major noncommunicable disease with a significant increase in prevalence, especially in low- and middle-income countries. The latest International Diabetes Federation Diabetes Atlas (2025) reports that 11.1% of ...

Linking Patient-Reported and Clinician-Assessed Wound Status via Chatbot-Based Digital Surveillance for Wound Infection: Retrospective Observational Study.

JMIR formative research
BACKGROUND: Digital wound monitoring has become increasingly feasible with the widespread use of smartphones and mobile messaging platforms. Although most previous studies have focused on chronic wounds and demonstrated the clinical benefits of remot...

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...

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...