AIMC Topic: Middle Aged

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A multinational study of deep learning-based image enhancement for multiparametric glioma MRI.

Scientific reports
This study aimed to validate the utility of commercially available vendor-neutral deep learning (DL) image enhancement software for improving the image quality of multiparametric MRI for gliomas in a multinational setting. A total of 294 patients fro...

End-to-end CNN-based deep learning enhances breast lesion characterization using quantitative ultrasound (QUS) spectral parametric images.

Scientific reports
QUS spectral parametric imaging offers a fast and accurate method for breast lesion characterization. This study explored using deep CNNs to classify breast lesions from QUS spectral parametric images, aiming to enhance radiomics and conventional mac...

The socio-economic impact of robotic prosthetics: the Hannes hand case study.

Scientific reports
Social impact assessment has gained increasing attention in recent years, emphasizing the added value and social changes brought by project activities alongside the sustainability of social actions. This study evaluates the economic and social impact...

Automated segmentation of brain metastases in magnetic resonance imaging using deep learning in radiotherapy.

Scientific reports
Brain metastases (BMs) are the most common intracranial tumors and stereotactic radiotherapy improved the life quality of patient with BMs, while it requires more time and experience to delineate BMs precisely by oncologists. Deep Learning techniques...

Autonomous artificial intelligence prescribing a drug to prevent severe acute graft-versus-host disease in HLA-haploidentical transplants.

Nature communications
Autonomous artificial intelligence (AI) models for deciding treatment strategies are available but rarely applied prospectively in clinical settings. Here we present a prospective study of deploying daGOAT, an algorithm we have developed, as a condit...

Ratio of haemorrhagic area to retinal area as a novel indicator for AI-based screening of diabetic retinopathy in type 2 diabetes: a community-based cross-sectional study.

BMJ open
BACKGROUND: The application of artificial intelligence (AI) technology in the screening of diabetic retinopathy (DR) has made significant strides. However, there remains a lack of comprehensive validation and evaluation of AI-derived quantitative ind...

Single-centre, prospective cohort to predict optimal individualised treatment response in multiple sclerosis (POINT-MS): a cohort profile.

BMJ open
PURPOSE: Multiple sclerosis (MS) is a chronic neurological condition that affects approximately 150 000 people in the UK and presents a significant healthcare burden, including the high costs of disease-modifying treatments (DMTs). DMTs have substant...

Harnessing the Power of Technology to Transform Delirium Severity Measurement in the Intensive Care Unit: Protocol for a Prospective Cohort Study.

JMIR research protocols
BACKGROUND: Delirium, an acute brain dysfunction, is a complication in up to 50% of patients in the intensive care unit (ICU). Measuring and mitigating delirium severity can reduce associated morbidity and improve long-term health outcomes post disch...

Testing the Acceptability and Feasibility of a Gender-Informed Smoking Cessation mHealth App for Women: Mixed Methods Approach.

JMIR human factors
BACKGROUND: Cigarette smoking is a leading cause of preventable morbidity and mortality worldwide. Women who smoke face greater health risks than men, including higher rates of cardiovascular disease and more pronounced declines in lung function. Des...

Predicting postoperative fever in culture-negative patients undergoing mini-PCNL using MAP score-augmented machine learning: a retrospective cohort study.

World journal of urology
PURPOSE: Postoperative fever is a common complication following percutaneous nephrolithotomy (PCNL) that occurs even in patients with sterile urine cultures. Traditional risk-assessment tools are insufficient in this subset of patients. This study ai...