AIMC Topic: Reproducibility of Results

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Ensemble Learning with Supervised Methods Based on Large-Scale Protein Language Models for Protein Mutation Effects Prediction.

International journal of molecular sciences
Machine learning has been increasingly utilized in the field of protein engineering, and research directed at predicting the effects of protein mutations has attracted increasing attention. Among them, so far, the best results have been achieved by r...

Reliability and validity of a widely-available AI tool for assessment of stress based on speech.

Scientific reports
Cigna's online stress management toolkit includes an AI-based tool that purports to evaluate a person's psychological stress level based on analysis of their speech, the Cigna StressWaves Test (CSWT). In this study, we evaluate the claim that the CSW...

Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance.

Investigative radiology
OBJECTIVE: The aim of this study was to evaluate the impact of ultra-high-resolution acquisition and deep learning reconstruction (DLR) on the image quality and diagnostic performance of T2-weighted periodically rotated overlapping parallel lines wit...

Differentiation Between Glioblastoma and Metastatic Disease on Conventional MRI Imaging Using 3D-Convolutional Neural Networks: Model Development and Validation.

Academic radiology
RATIONALE AND OBJECTIVES: Imaging-based differentiation between glioblastoma (GB) and brain metastases (BM) remains challenging. Our aim was to evaluate the performance of 3D-convolutional neural networks (CNN) to address this binary classification p...

Leveraging ChatGPT for ophthalmic education: A critical appraisal.

European journal of ophthalmology
In recent years, the advent of artificial intelligence (AI) has transformed many sectors, including medical education. This editorial critically appraises the integration of ChatGPT, a state-of-the-art AI language model, into ophthalmic education, fo...

Cephalometric landmark detection without X-rays combining coordinate regression and heatmap regression.

Scientific reports
Fully automated techniques using convolutional neural networks for cephalometric landmark detection have recently advanced. However, all existing studies have adopted X-rays. The problem of direct exposure of patients to X-ray radiation remains unsol...

MRI-based automated multitask deep learning system to evaluate supraspinatus tendon injuries.

European radiology
OBJECTIVE: To establish an automated, multitask, MRI-based deep learning system for the detailed evaluation of supraspinatus tendon (SST) injuries.

Computational prediction of complex cationic rearrangement outcomes.

Nature
Recent years have seen revived interest in computer-assisted organic synthesis. The use of reaction- and neural-network algorithms that can plan multistep synthetic pathways have revolutionized this field, including examples leading to advanced natur...