AIMC Topic: Aged

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Social robot for at-home cognitive monitoring.

Science robotics
A socially assistive robot can administer in-home neuropsychological tests for cognitive monitoring of older adults.

Evaluation and analysis of risk factors for adverse events of the fractured vertebra post-percutaneous kyphoplasty: a retrospective cohort study using multiple machine learning models.

Journal of orthopaedic surgery and research
BACKGROUND: Adverse events of the fractured vertebra (AEFV) post-percutaneous kyphoplasty (PKP) can lead to recurrent pain and neurological damage, which considerably affect the prognosis of patients and the quality of life. This study aimed to analy...

PD-ARnet: a deep learning approach for Parkinson's disease diagnosis from resting-state fMRI.

Journal of neural engineering
. The clinical diagnosis of Parkinson's disease (PD) relying on medical history, clinical symptoms, and signs is subjective and lacks sensitivity. Resting-state fMRI (rs-fMRI) has been demonstrated to be an effective biomarker for diagnosing PD.This ...

Evaluation of Sociomedical Factors on Corneal Donor Recovery Using Machine Learning.

Ophthalmic epidemiology
PURPOSE: To evaluate co-morbid sociomedical conditions affecting corneal donor endothelial cell density and transplant suitability.

The Potential Clinical Utility of an Artificial Intelligence Model for Identification of Vertebral Compression Fractures in Chest Radiographs.

Journal of the American College of Radiology : JACR
PURPOSE: To assess the ability of the Annalise Enterprise CXR Triage Trauma (Annalise AI Pty Ltd, Sydney, NSW, Australia) artificial intelligence model to identify vertebral compression fractures on chest radiographs and its potential to address undi...

Deep Learning Model for Pathological Grading and Prognostic Assessment of Lung Cancer Using CT Imaging: A Study on NLST and External Validation Cohorts.

Academic radiology
RATIONALE AND OBJECTIVES: To develop and validate a deep learning model for automated pathological grading and prognostic assessment of lung cancer using CT imaging, thereby providing surgeons with a non-invasive tool to guide surgical planning.

Can the preoperative CT-based deep learning radiomics model predict histologic grade and prognosis of chondrosarcoma?

European journal of radiology
BACKGROUND AND PURPOSE: Computed tomography (CT) and biopsy may be insufficient for preoperative evaluation of the grade and outcome of patients with chondrosarcoma. The aim of this study was to develop and validate a CT-based deep learning radiomics...

A natural language processing-informed adrenal gland incidentaloma clinic improves guideline-based care.

World journal of surgery
INTRODUCTION: Adrenal gland incidentalomas (AGIs) are found in up to 5% of cross-sectional images. However, rates of guideline-based workup for AGIs are notoriously low. We sought to determine if a natural language processing (NLP)-informed AGI clini...

Application of machine learning algorithms to predict postoperative surgical site infections and surgical site occurrences following inguinal hernia surgery.

Hernia : the journal of hernias and abdominal wall surgery
PURPOSE: This study aimed to develop, validate, and evaluate machine learning (ML) algorithms for predicting Surgical site infections (SSI) and surgical site occurrences (SSO) after elective open inguinal hernia surgery.

[Development and validation of a tool for the systematic identification of social vulnerabilities in cancer patients: the DEFCO tool].

Bulletin du cancer
INTRODUCTION: Literature suggests that patients from deprived backgrounds are less likely to adhere to their treatments, continue to expose themselves to risk factors and, as a result, have poorer health outcomes. It is therefore crucial to identify ...