AIMC Topic: Aged

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Machine Learning Models for Classifying Physical Activity in Free-Living Preschool Children.

Sensors (Basel, Switzerland)
Machine learning (ML) activity classification models trained on laboratory-based activity trials exhibit low accuracy under free-living conditions. Training new models on free-living accelerometer data, reducing the number of prediction windows compr...

Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: This study aims to identify robust radiomic features for Magnetic Resonance Imaging (MRI), assess feature selection and machine learning methods for overall survival classification of Glioblastoma multiforme patients, and to robustify mod...

Dr. Answer AI for prostate cancer: Clinical outcome prediction model and service.

PloS one
OBJECTIVES: The importance of clinical outcome prediction models using artificial intelligence (AI) is being emphasized owing to the increasing necessity of developing a clinical decision support system (CDSS) employing AI. Therefore, in this study, ...

Development and validation of an explainable artificial intelligence-based decision-supporting tool for prostate biopsy.

BJU international
OBJECTIVES: To develop and validate a risk calculator for prostate cancer (PCa) and clinically significant PCa (csPCa) using explainable artificial intelligence (XAI).

Predicting Alzheimer's disease progression using deep recurrent neural networks.

NeuroImage
Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is important for developing disease-modifying therapies. In this study, given multimodal AD markers and clinical diagnosis of an individual from one or more t...

Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Community-acquired acute kidney injury (CA-AKI)-associated hospitalizations impose significant health care needs and contribute to in-hospital mortality. However, most risk prediction models developed to date have focused on AKI in a spec...

Development and validation of prognosis model of mortality risk in patients with COVID-19.

Epidemiology and infection
This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective study of the inpatients with COVID-19 admitted from 15 January to 15 Mar...

PSA-based machine learning model improves prostate cancer risk stratification in a screening population.

World journal of urology
CONTEXT: The majority of prostate cancer diagnoses are facilitated by testing serum Prostate Specific Antigen (PSA) levels. Despite this, there are limitations to the diagnostic accuracy of PSA. Consideration of patient demographic factors and bioche...

Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury.

JAMA network open
IMPORTANCE: Acute kidney injury (AKI) is associated with increased morbidity and mortality in hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and few prediction models have been externally validated.