AIMC Topic: Aged

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Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

PloS one
BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation and treatment response. Identifying distinct subphenotypes of HTN may improve our understanding of its underlying mechanisms and guide more precise t...

Multiparameter MRI-based automatic segmentation and diagnostic models for the differentiation of intracranial solitary fibrous tumors and meningiomas.

Annals of medicine
BACKGROUND: Intracranial solitary fibrous tumors (SFTs) and meningiomas are meningeal tumors with different malignancy levels and prognoses. Their similar imaging features make preoperative differentiation difficult, resulting in high misdiagnosis ra...

The correlation of liquid biopsy genomic data to radiomics in colon, pancreatic, lung and prostatic cancer patients.

European journal of cancer (Oxford, England : 1990)
INTRODUCTION: With the advances in artificial intelligence (AI) and precision medicine, radiomics has emerged as a promising tool in the field of oncology. Radiogenomics integrates radiomics with genomic data, potentially offering a non-invasive meth...

Artificial intelligence-assisted nursing in cancer care: A meta-analysis of its impact on pain, anxiety, and quality of life.

Applied nursing research : ANR
BACKGROUND: In recent years, artificial intelligence (AI) applications have been recognized as a supportive technological method for effectively managing the challenges faced by patients with cancer. AI applications are anticipated to be beneficial i...

Protocol for the REBOUND study: a cohort study to uncover fundamental mechanisms of accelerated ageing and impaired resilience following cancer surgery and treatment.

BMC geriatrics
BACKGROUND: Ageing is a heterogeneous process, which is associated with heterogeneous resilience in older people. Cancer surgery and treatment may be associated with accelerated ageing in some older people; studying this process will improve understa...

Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease.

Scientific reports
Advanced metabolic-dysfunction-associated steatotic liver disease (MASLD) fibrosis (F3-4) predicts liver-related outcomes. Serum and elastography-based non-invasive tests (NIT) cannot yet reliably predict MASLD outcomes. The role of B-mode ultrasound...

AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view.

Scientific reports
This study aims to enhance the dosimetry accuracy in I planar imaging by utilizing a single oblique view and Monte Carlo (MC) validated dose point kernels (DPKs) alongside the integration of artificial intelligence (AI) for accurate dose prediction w...

Development and Validation of a Rule-Based Natural Language Processing Algorithm to Identify Falls in Inpatient Records of Older Adults: Retrospective Analysis.

JMIR aging
BACKGROUND: In order to address fall underestimation by the International Classification of Diseases (ICD) in clinical settings, information from clinical notes could be incorporated via natural language processing (NLP) as a possible solution. Howev...

Evaluating cell-free DNA integrity index as a non-invasive biomarker for neoadjuvant chemotherapy in colorectal cancer patients.

BMC cancer
BACKGROUND: Neoadjuvant chemotherapy (NAC) is gaining attention as a treatment for advanced colorectal cancer owing to its potential to improve surgical outcomes and prognosis. However, reliable biomarkers to predict the response to NAC are lacking. ...

Artificial intelligence in nutrition and ageing research - A primer on the benefits.

Maturitas
Artificial intelligence (AI) is increasingly impacting multiple domains. The application of AI in nutrition and ageing research has significant potential to transform healthcare outcomes for the ageing population. This review provides critical insigh...