AIMC Topic: Aged

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Care home resident identification: A comparison of address matching methods with Natural Language Processing.

PloS one
BACKGROUND: Care home residents are a highly vulnerable group, but identifying care home residents in routine data is challenging. This study aimed to develop and validate Natural Language Processing (NLP) methods to identify care home residents from...

A machine-learning model for prediction of Acinetobacter baumannii hospital acquired infection.

PloS one
BACKGROUND: Acinetobacter baumanni infection is a leading cause of morbidity and mortality in the Intensive Care Unit (ICU). Early recognition of patients at risk for infection allows early proper treatment and is associated with improved outcomes. T...

Predicting progression-free survival in sarcoma using MRI-based automatic segmentation models and radiomics nomograms: a preliminary multicenter study.

Skeletal radiology
OBJECTIVES: Some sarcomas are highly malignant, associated with high recurrence despite treatment. This multicenter study aimed to develop and validate a radiomics signature to estimate sarcoma progression-free survival (PFS).

Using machine learning for personalized prediction of longitudinal coronavirus disease 2019 vaccine responses in transplant recipients.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
The coronavirus disease 2019 pandemic has underscored the importance of vaccines, especially for immunocompromised populations like solid organ transplant recipients, who often have weaker immune responses. The purpose of this study was to compare de...

A multimodal machine learning model for the stratification of breast cancer risk.

Nature biomedical engineering
Machine learning models for the diagnosis of breast cancer can facilitate the prediction of cancer risk and subsequent patient management among other clinical tasks. For the models to impact clinical practice, they ought to follow standard workflows,...

Diagnostic Performance of Artificial Intelligence-Based Angiography-Derived Non-Hyperemic Pressure Ratio Using Pressure Wire as Reference.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: The angiography-derived non-hyperemic pressure ratio (angioNHPR) is a novel index of NHPR based on artificial intelligence (AI) that does not require pressure wires. We investigated the diagnostic accuracy of angioNHPR for detecting hemod...

Deep learning-based overall survival prediction in patients with glioblastoma: An automatic end-to-end workflow using pre-resection basic structural multiparametric MRIs.

Computers in biology and medicine
PURPOSE: Accurate and automated early survival prediction is critical for patients with glioblastoma (GBM) as their poor prognosis requires timely treatment decision-making. To address this need, we developed a deep learning (DL)-based end-to-end wor...

Artificial intelligence for identification of candidates for device-aided therapy in Parkinson's disease: DELIST-PD study.

Computers in biology and medicine
INTRODUCTION: In Parkinson's Disease (PD), despite available treatments focusing on symptom alleviation, the effectiveness of conventional therapies decreases over time. This study aims to enhance the identification of candidates for device-aided the...