AIMC Topic: Aged
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Development and validation of an interpretable machine learning model to predict major adverse cardiovascular events after noncardiac surgery in geriatric patients: a prospective study.
International journal of surgery (London, England)
Feb 1, 2025
BACKGROUND: Major adverse cardiovascular events (MACEs) within 30 days following noncardiac surgery are prognostically relevant. Accurate prediction of risk and modifiable risk factors for postoperative MACEs is critical for surgical planning and pat...
Predicting early recurrence in locally advanced gastric cancer after gastrectomy using CT-based deep learning model: a multicenter study.
International journal of surgery (London, England)
Feb 1, 2025
BACKGROUND: Early recurrence in patients with locally advanced gastric cancer (LAGC) portends aggressive biological characteristics and a dismal prognosis. Predicting early recurrence may help determine treatment strategies for LAGC. The goal is to d...
Machine learning-based risk prediction of mild cognitive impairment in patients with chronic heart failure: A model development and validation study.
Geriatric nursing (New York, N.Y.)
Feb 1, 2025
Accurate identification of individuals at high risk for mild cognitive impairment (MCI) among chronic heart failure (CHF) patients is crucial for reducing rehospitalization and mortality rates. This study aimed to develop and validate a machine learn...
Development of a machine learning model and a web application for predicting neurological outcome at hospital discharge in spinal cord injury patients.
The spine journal : official journal of the North American Spine Society
Jan 31, 2025
BACKGROUND: Spinal cord injury (SCI) is a devastating condition with profound physical, psychological, and socioeconomic consequences. Despite advances in SCI treatment, accurately predicting functional recovery remains a significant challenge. Conve...
External validation of 12 existing survival prediction models for patients with spinal metastases.
The spine journal : official journal of the North American Spine Society
Jan 31, 2025
BACKGROUND CONTEXT: Survival prediction models for patients with spinal metastases may inform patients and clinicians in shared decision-making.
Smart home-assisted anomaly detection system for older adults: a deep learning approach with a comprehensive set of daily activities.
Medical & biological engineering & computing
Jan 31, 2025
Smart homes have the potential to enable remote monitoring of the health and well-being of older adults, leading to improved health outcomes and increased independence. However, current approaches only consider a limited set of daily activities and d...
A novel artificial intelligence framework to quantify the impact of clinical compared with nonclinical influences on postoperative length of stay.
Surgery
Jan 31, 2025
BACKGROUND: The relative proportion of clinical compared with nonclinical influences on length of stay after colectomy has never been measured. We developed a novel machine-learning framework that quantifies the proportion of length of stay after col...
Machine learning model for predicting DIBH non-eligibility in left-sided breast cancer radiotherapy: Development, validation and clinical impact analysis.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jan 31, 2025
OBJECTIVE: Multi-day assessments accurately identify patients with left-sided breast cancer who are ineligible for irradiation in Deep Inspiration Breath Hold (DIBH) and minimise on-couch treatment time in those who are eligible. The challenge of imp...
Multiscale deep learning radiomics for predicting recurrence-free survival in pancreatic cancer: A multicenter study.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jan 31, 2025
PURPOSE: This multicenter study aimed to develop and validate a multiscale deep learning radiomics nomogram for predicting recurrence-free survival (RFS) in patients with pancreatic ductal adenocarcinoma (PDAC).
Integrating neuroscience and artificial intelligence: EEG analysis using ensemble learning for diagnosis Alzheimer's disease and frontotemporal dementia.
Journal of neuroscience methods
Jan 31, 2025
BACKGROUND: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are both progressive neurological disorders that affect the elderly. Distinguishing between individuals suffering from these two diseases in the early stages can be quite challeng...
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