AIMC Topic: Reproducibility of Results

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Open-radiomics: a collection of standardized datasets and a technical protocol for reproducible radiomics machine learning pipelines.

BMC medical imaging
BACKGROUND: As an important branch of machine learning pipelines in medical imaging, radiomics faces two major challenges namely reproducibility and accessibility. In this work, we introduce open-radiomics, a set of radiomics datasets along with a co...

Histopathological-based brain tumor grading using 2D-3D multi-modal CNN-transformer combined with stacking classifiers.

Scientific reports
Reliability in diagnosing and treating brain tumors depends on the accurate grading of histopathological images. However, limited scalability, adaptability, and interpretability challenge current methods for frequently grading brain tumors to accurat...

Machine Learning-Based Cognitive Assessment With The Autonomous Cognitive Examination: Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: The rising prevalence of dementia necessitates a scalable solution to cognitive assessments. The Autonomous Cognitive Examination (ACoE) is a foundational cognitive test for the phenotyping of cognitive symptoms across the primary cogniti...

K-Means Clustering and Classification of Breast Cancer Images Using Histogram of Oriented Gradients Features and Convolutional Neural Network Models: Diagnostic Image Analysis Study.

JMIR formative research
BACKGROUND: Breast cancer has proven to be the most common type of cancer among females around the world. However, mortality rates can be reduced if it is diagnosed at the initial stages. Interpretation made by an expert is required by conventional d...

A comparison of quality and readability of Artificial Intelligence chatbots in triage for head and neck cancer.

American journal of otolaryngology
OBJECTIVE: Head and neck cancers (HNCs) are a significant global health concern, contributing to substantial morbidity and mortality. AI-powered chatbots such as ChatGPT, Google Gemini, Microsoft Copilot, and Open Evidence are increasingly used by pa...

Evaluating Large Language Models for imaging modality selection: Potential to reduce unnecessary contrast agent use and radiation exposure.

Clinical imaging
INTRODUCTION: Large Language Models (LLMs) represent a transformative leap in artificial intelligence with the potential to revolutionize radiologic decision-making. This study uniquely evaluates the performance of various LLMs from different vendors...

Development and validation of deep learning for predicting the growth of ovarian cancer organoids.

Chinese medical journal
BACKGROUND: Organoids have attracted enormous interest in disease modeling, drug screening, and precision medicine. However, developing robust patient-derived organoids (PDOs) was time-consuming, costly, and had low success rates for certain cancer t...

A multi-omic single-cell landscape reveals transcription and epigenetic regulatory features of t(8;21) AML.

Journal of translational medicine
BACKGROUND: Comprehensive analysis of single-cell transcriptome and chromatin accessibility will contribute to interpret the heterogeneity of acute myeloid leukemia (AML). We hypothesize that integrating single-cell transcriptomic and chromatin acces...

Discrepancies between plantar pressure devices: Evaluating cross-system reliability for biomechanics, clinical use and predictive modelling.

Foot (Edinburgh, Scotland)
Plantar pressure measurement systems are widely used to assess foot function and gait, yet discrepancies in sensor design, measurement protocols, and population characteristics can undermine data comparability. This study investigated three platform‑...