AIMC Topic: Reproducibility of Results

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Full-scale representation guided network for retinal vessel segmentation.

BMC medical imaging
The U-Net architecture and its variants have remained state-of-the-art (SOTA) for retinal vessel segmentation over the past decade. In this study, we introduce a Full-Scale Guided Network (FSG-Net), where a novel feature representation module using m...

Evaluating the reliability and clinical utility of artificial intelligence in first trimester prenatal screening and noninvasive prenatal testing.

Scientific reports
Artificial intelligence (AI) tools like ChatGPT-4o are increasingly utilized in prenatal care. However, their reliability and clinical applicability for healthcare providers in first-trimester screening remain unclear. This study aimed to evaluate th...

Deriving three one dimensional NMR spectra from a single experiment through machine learning.

Nature communications
Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful tool for analyzing complex mixtures due to its ability to manage matrix complexity, provide detailed molecular insights, and preserve sample integrity. In metabolomics, NMR enables the ident...

Comparative performance of large language models in answering periodontology questions from the Turkish Dental Specialty Examination: a cross-sectional study on accuracy and coverage.

BMC oral health
BACKGROUND: In recent years, several studies have explored the use of large language models (LLMs) such as ChatGPT-4, Claude, Gemini Advanced, and DeepSeek-R1 in dental education. Nevertheless, no study has yet reported a comparative evaluation of mu...

Distinct immune-metabolic phenotypes underlie poor coronary collateral circulation.

Cardiovascular diabetology
BACKGROUND: Coronary collateral circulation (CCC) significantly impacts myocardial perfusion and clinical outcomes in coronary artery disease patients, yet the underlying molecular heterogeneity remains inadequately characterized.

Enhancing automatic diagnosis of thyroid nodules from ultrasound scans leveraging deep learning models.

Scientific reports
The thyroid gland is prone to various diseases, including thyroid nodules. Ultrasound is the primary diagnostic tool, but classification accuracy is often limited by radiologist expertise. Integrating Artificial Intelligence, particularly Deep Learni...

A novel adaptive sigma KNN model for depression and anxiety detection following the COVID 19 pandemic.

Scientific reports
Mental health disorders, such as depression and anxiety, are increasing, and thus, there is a necessity for accurate and effective detection. K-Nearest Neighbors (KNN) and extensions have been extensively used in disease detection. In this work, Adap...

Full title: evaluating AI guidelines in leading family medicine journals: a cross-sectional study.

BMC primary care
BACKGROUND: Artificial intelligence (AI) is increasingly integrated into family medicine research and practice, enhancing diagnostics, data analysis, and care delivery. Yet, its rapid adoption has outpaced the development of standardized editorial po...

Evaluating the Accuracy of the Frysian Questionnaire for Differentiation of Musculoskeletal Complaints for Triage of Musculoskeletal Diseases: Algorithm Development and Validation Study.

JMIR medical informatics
BACKGROUND: Inflammatory rheumatic diseases (IRDs) affect 5% of the general population, whereas 35% of the population experiences musculoskeletal concerns. IRDs cause early disability, reduced life expectancy, and considerable health care costs. Earl...

Machine learning-based prediction model for omental metastasis in right-sided colon cancer patients: a retrospective multicenter study.

International journal of colorectal disease
PURPOSE: Current diagnostic modalities lack sufficient sensitivity for detecting omental metastasis (OM), often underestimating metastatic burden. Unlike traditional statistical model, machine learning (ML) model is designed to detect subtle variable...