AIMC Topic: Reproducibility of Results

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A fully automated artificial intelligence-driven software for planning of transcatheter aortic valve replacement.

Cardiovascular revascularization medicine : including molecular interventions
BACKGROUND: Transcatheter aortic valve replacement (TAVR) is increasingly performed for the treatment of aortic stenosis. Computed tomography (CT) analysis is essential for pre-procedural planning. Currently available software packages for TAVR plann...

Differentiation of testicular seminomas from nonseminomas based on multiphase CT radiomics combined with machine learning: A multicenter study.

European journal of radiology
BACKGROUND: Differentiating seminomas from nonseminomas is crucial for formulating optimal treatment strategies for testicular germ cell tumors (TGCTs). Therefore, our study aimed to develop and validate a clinical-radiomics model for this purpose.

Intelligence Sparse Sensor Network for Automatic Early Evaluation of General Movements in Infants.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
General movements (GMs) have been widely used for the early clinical evaluation of infant brain development, allowing immediate evaluation of potential development disorders and timely rehabilitation. The infants' general movements can be captured di...

Justice at the Forefront: Cultivating felt accountability towards Artificial Intelligence among healthcare professionals.

Social science & medicine (1982)
The advent of AI has ushered in a new era of patient care, but with it emerges a contentious debate surrounding accountability for algorithmic medical decisions. Within this discourse, a spectrum of views prevails, ranging from placing accountability...

Building trust in deep learning-based immune response predictors with interpretable explanations.

Communications biology
The ability to predict whether a peptide will get presented on Major Histocompatibility Complex (MHC) class I molecules has profound implications in designing vaccines. Numerous deep learning-based predictors for peptide presentation on MHC class I m...

Artificial intelligence and illusions of understanding in scientific research.

Nature
Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of ...

DDParcel: Deep Learning Anatomical Brain Parcellation From Diffusion MRI.

IEEE transactions on medical imaging
Parcellation of anatomically segregated cortical and subcortical brain regions is required in diffusion MRI (dMRI) analysis for region-specific quantification and better anatomical specificity of tractography. Most current dMRI parcellation approache...

Assessing the proficiency of artificial intelligence programs in the diagnosis and treatment of cornea, conjunctiva, and eyelid diseases and exploring the advantages of each other benefits.

Contact lens & anterior eye : the journal of the British Contact Lens Association
PURPOSE: It was aimed to determine the knowledge level of ChatGPT, Bing, and Bard artificial intelligence programs related to corneal, conjunctival, and eyelid diseases and treatment modalities, to examine their reliability and superiority to each ot...