AIMC Topic: Aged
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A Novel Implementation of a Social Robot for Sustainable Human Engagement in Homecare Services for Ageing Populations.
Sensors (Basel, Switzerland)
Jul 10, 2024
This research addresses the rapid aging phenomenon prevalent in Asian societies, which has led to a significant increase in elderly individuals relocating to nursing homes due to health-related issues. This trend has resulted in social isolation and ...
A proof of concept for microcirculation monitoring using machine learning based hyperspectral imaging in critically ill patients: a monocentric observational study.
Critical care (London, England)
Jul 10, 2024
BACKGROUND: Impaired microcirculation is a cornerstone of sepsis development and leads to reduced tissue oxygenation, influenced by fluid and catecholamine administration during treatment. Hyperspectral imaging (HSI) is a non-invasive bedside technol...
Prediction of COVID-19 patients' participation in financing informal care using machine learning methods: willingness to pay and willingness to accept approaches.
BMC health services research
Jul 10, 2024
BACKGROUND: Informal care plays an essential role in managing the COVID-19 pandemic. Expanding health insurance packages that reimburse caregivers' services through cost-sharing policies could increase financial resources. Predicting payers' willingn...
Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra.
Scientific reports
Jul 10, 2024
Raman spectroscopy is a rapid method for analysing the molecular composition of biological material. However, noise contamination in the spectral data necessitates careful pre-processing prior to analysis. Here we propose an end-to-end Convolutional ...
Habitat radiomics and deep learning fusion nomogram to predict EGFR mutation status in stage I non-small cell lung cancer: a multicenter study.
Scientific reports
Jul 10, 2024
Develop a radiomics nomogram that integrates deep learning, radiomics, and clinical variables to predict epidermal growth factor receptor (EGFR) mutation status in patients with stage I non-small cell lung cancer (NSCLC). We retrospectively included ...
Unlocking Optimal Glycemic Interpretation: Redefining HbA1c Analysis in Female Patients With Diabetes and Iron-Deficiency Anemia Using Machine Learning Algorithms.
Journal of clinical laboratory analysis
Jul 10, 2024
OBJECTIVE: In response to the nuanced glycemic challenges faced by women with iron deficiency anemia (IDA) associated with diabetes, this study uses advanced machine learning algorithms to redefine hemoglobin (Hb)A1c measurement values. We aimed to i...
Deep learning for predicting rehospitalization in acute heart failure: Model foundation and external validation.
ESC heart failure
Jul 9, 2024
AIMS: Assessing the risk for HF rehospitalization is important for managing and treating patients with HF. To address this need, various risk prediction models have been developed. However, none of them used deep learning methods with real-world data...
Evaluation of fragility fracture risk using deep learning based on ultrasound radio frequency signal.
Endocrine
Jul 9, 2024
BACKGROUND: It was essential to identify individuals at high risk of fragility fracture and prevented them due to the significant morbidity, mortality, and economic burden associated with fragility fracture. The quantitative ultrasound (QUS) showed p...
The role of biomarkers and dosimetry parameters in overall and progression free survival prediction for patients treated with personalized Y glass microspheres SIRT: a preliminary machine learning study.
European journal of nuclear medicine and molecular imaging
Jul 9, 2024
BACKGROUND: Overall Survival (OS) and Progression-Free Survival (PFS) analyses are crucial metrics for evaluating the efficacy and impact of treatment. This study evaluated the role of clinical biomarkers and dosimetry parameters on survival outcomes...
Uncovering STEMI patient phenotypes using unsupervised machine learning.
International journal of cardiology
Jul 9, 2024
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