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Accuracy and safety of ChatGPT-4o responses in rhinoplasty postoperative counseling: a panel-based study.

Acta oto-laryngologica
BACKGROUND: ChatGPT and other large language models have emerged as new tools for patient education, yet their clinical safety and reliability remain unclear.

The analysis of interactive furniture design system based on artificial intelligence.

Scientific reports
To enhance user interaction experience in furniture customization, this study optimizes an Internet of Things (IoT)-driven Artificial Intelligence (AI)-assisted design system. First, the study analyzes human-computer interaction theories in IoT envir...

Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer's disease progression.

Alzheimer's research & therapy
BACKGROUND: Alzheimer's disease (AD) is the principal cause of dementia and requires the early diagnosis of people with mild cognitive impairment (MCI) who are at high risk of progressing. Early diagnosis is imperative for optimizing clinical managem...

Machine learning based classification of catastrophic health expenditures: a cross-sectional study of Korean low-income households.

BMC health services research
BACKGROUND: Despite the National Health Insurance (NHI) system implemented in South Korea, concerns persist regarding access to health coverage for low-income households. To address this issue, this study aims to use machine learning-based data minin...

Remote clinical decision support tool for Parkinson's disease assessment using a novel approach that combines AI and clinical knowledge.

BMC medical informatics and decision making
BACKGROUND: Early diagnosis of Parkinson's disease (PD) can assist in designing efficient treatments. Reduced facial expressions are considered a hallmark of PD, making advanced artificial intelligence (AI) image processing a potential non-invasive c...

Urinary Complement proteome strongly linked to diabetic kidney disease progression.

Nature communications
Diabetic kidney disease (DKD) progression is not well understood. Using high-throughput proteomics, biostatistical, pathway and machine learning tools, we examine the urinary Complement proteome in two prospective cohorts with type 1 or 2 diabetes an...

Explainable illicit drug abuse prediction using hematological differences.

Scientific reports
This study aimed to develop a reliable and explainable predictive model for illicit drug use (IDU). The model uses a machine learning (ML) algorithm to predict IDU using hematological differences between illicit drug users (IDUr) and non-users (n-IDU...

Quantitative image analysis of the extracellular matrix of esophageal squamous cell carcinoma and high grade dysplasia via two-photon microscopy.

Scientific reports
Squamous cell carcinoma (SCC) and high-grade dysplasia (HGD) are two different pathological entities; however, they sometimes share similarities in histological structure depending on the context. Thus, distinguishing between the two may require care...

Phenotype augmentation using generative AI for isocitrate dehydrogenase mutation prediction in glioma.

Scientific reports
This study investigated the effects of feature augmentation, which uses generated images with specific imaging features, on the performance of isocitrate dehydrogenase (IDH) mutation prediction models in gliomas. A total of 598 patients were included...

Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma.

Scientific reports
The mortality rates have been increasing for glioma in adolescents and young adults (AYAs, aged 15-39 years). However, current biomarkers for clinical assessment in AYAs glioma are limited, prompting the urgent need for identifying ideal prognostic s...