AI Medical Compendium Topic

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Reproducibility of Results

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Enhancing Malignancy Detection and Tumor Classification in Pathology Reports: A Comparative Evaluation of Large Language Models.

Studies in health technology and informatics
BACKGROUND: Cancer registries require accurate and efficient documentation of malignancies, yet current manual methods are time-consuming and error-prone.

Reliability of Emotion Analysis from Human Facial Expressions Using Multi-task Cascaded Convolutional Neural Networks.

The journal of medical investigation : JMI
Life support robots in care settings must be able to read a person's emotions from facial expressions to achieve empathic communication. This study aims to determine the degree of agreement between Multi-task Cascaded Convolutional Neural Networks (M...

Development and Validation of the Novel Exergame-Integrated Robotic Stepper Device for Seated Lower Limb Rehabilitation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Seated rehabilitation is essential in early-stage recovery for patients who can sit but cannot stand or walk. Robotic-based lower limb rehabilitation provides precise, task-specific training for recovery, but its application in seated exercises remai...

Multiple instance learning-based prediction of programmed death-ligand 1 (PD-L1) expression from hematoxylin and eosin (H&E)-stained histopathological images in breast cancer.

PeerJ
Programmed death-ligand 1 (PD-L1) is an important biomarker increasingly used as a predictive marker in breast cancer immunotherapy. Immunohistochemical quantification remains the standard method for assessment. However, it presents challenges relate...

Identification and validation of HOXC6 as a diagnostic biomarker for Ewing sarcoma: insights from machine learning algorithms and experiments.

Frontiers in immunology
INTRODUCTION: Early diagnosis of Ewing sarcoma (ES) is critical for improving patient prognosis. However, the accurate diagnosis of ES remains challenging, underscoring the need for novel diagnostic biomarkers to enhance diagnostic precision and reli...

Comparison of machine learning models with conventional statistical methods for prediction of percutaneous coronary intervention outcomes: a systematic review and meta-analysis.

BMC cardiovascular disorders
INTRODUCTION: Percutaneous coronary intervention (PCI) has been the main treatment of coronary artery disease (CAD). In this review, we aimed to compare the performance of machine learning (ML) vs. logistic regression (LR) models in predicting differ...

AI-supported approaches for mammography single and double reading: A controlled multireader study.

European journal of radiology
PURPOSE: To assess the impact of artificial intelligence (AI) on the diagnostic performance of radiologists with varying experience levels in mammography reading, considering single and simulated double reading approaches.

Deep learning-driven multi-class classification of brain strokes using computed tomography: A step towards enhanced diagnostic precision.

European journal of radiology
OBJECTIVE: To develop and validate deep learning models leveraging CT imaging for the prediction and classification of brain stroke conditions, with the potential to enhance accuracy and support clinical decision-making.

Keeping AI on Track: Regular monitoring of algorithmic updates in mammography.

European journal of radiology
PURPOSE: To demonstrate a method of benchmarking the performance of two consecutive software releases of the same commercial artificial intelligence (AI) product to trained human readers using the Personal Performance in Mammographic Screening scheme...

Comparative analysis of heart disease prediction using logistic regression, SVM, KNN, and random forest with cross-validation for improved accuracy.

Scientific reports
This primary research paper emphasizes cross-validation, where data samples are reshuffled in each iteration to form randomized subsets divided into n folds. This method improves model performance and achieves higher accuracy than the baseline model....