AIMC Topic: Middle Aged

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Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.

The Journal of clinical endocrinology and metabolism
CONTEXT: Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive.

segcsvd: A Convolutional Neural Network-Based Tool for Quantifying White Matter Hyperintensities in Heterogeneous Patient Cohorts.

Human brain mapping
White matter hyperintensities (WMH) of presumed vascular origin are a magnetic resonance imaging (MRI)-based biomarker of cerebral small vessel disease (CSVD). WMH are associated with cognitive decline and increased risk of stroke and dementia, and a...

The effectiveness of care robots in alleviating physical burden and pain for caregivers: Non-randomized prospective interventional study - Preliminary study.

Medicine
BACKGROUND: Caregiver burden significantly affects both patients and caregivers but is often overlooked in clinical practice. Physical and emotional strain on caregivers can compromise the quality of care. Care robots are emerging as solutions to all...

Evaluating the Impact of BoNT-A Injections on Facial Expressions: A Deep Learning Analysis.

Aesthetic surgery journal
BACKGROUND: Botulinum toxin type A (BoNT-A) injections are widely administered for facial rejuvenation, but their effects on facial expressions remain unclear.

A novel deep learning model for obstructive sleep apnea diagnosis: hybrid CNN-Transformer approach for radar-based detection of apnea-hypopnea events.

Sleep
STUDY OBJECTIVES: The demand for cost-effective and accessible alternatives to polysomnography (PSG), the conventional diagnostic method for obstructive sleep apnea (OSA), has surged. In this study, we have developed and validated a deep learning mod...

Novel machine learning technique further clarifies unrelated donor selection to optimize transplantation outcomes.

Blood advances
We investigated the impact of donor characteristics on outcomes in allogeneic hematopoietic cell transplantation (HCT) recipients using a novel machine learning approach, the Nonparametric Failure Time Bayesian Additive Regression Trees (NFT BART). N...

MALrisk: a machine-learning-based tool to predict imported malaria in returned travellers with fever.

Journal of travel medicine
BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence...

[A pilot study on clinical application of three-dimensional morphological completion of lesioned mandibles assisted by generative adversarial networks].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
To explore the clinical application pathway of the CT generative adversarial networks (CTGANs) algorithm in mandibular reconstruction surgery, aiming to provide a valuable reference for this procedure. A clinical exploratory study was conducted, 27...

Prediction of incident atrial fibrillation using deep learning, clinical models, and polygenic scores.

European heart journal
BACKGROUND AND AIMS: Deep learning applied to electrocardiograms (ECG-AI) is an emerging approach for predicting atrial fibrillation or flutter (AF). This study introduces an ECG-AI model developed and tested at a tertiary cardiac centre, comparing i...