Protein science : a publication of the Protein Society
Mar 1, 2024
Estimating the accuracy of protein structural models is a critical task in protein bioinformatics. The need for robust methods in the estimation of protein model accuracy (EMA) is prevalent in the field of protein structure prediction, where computat...
Biometrical journal. Biometrische Zeitschrift
Mar 1, 2024
When modeling competing risks (CR) survival data, several techniques have been proposed in both the statistical and machine learning literature. State-of-the-art methods have extended classical approaches with more flexible assumptions that can impro...
The Journal of orthopaedic and sports physical therapy
Mar 1, 2024
To compare the accuracy of an artificial intelligence chatbot to clinical practice guidelines (CPGs) recommendations for providing answers to complex clinical questions on lumbosacral radicular pain. Cross-sectional study. We extracted recommendat...
Reproducibility is important for having confidence in evolutionary machine learning algorithms. Although the focus of reproducibility is usually to recreate an aggregate prediction error score using fixed random seeds, this is not sufficient. Firstly...
The use of generative artificial intelligence (AI) applications such as ChatGPT is becoming increasingly popular. In Japan, consumers can purchase most over-the-counter (OTC) drugs without having to consult a pharmacist, so they may ask generative A...
European heart journal. Cardiovascular Imaging
Feb 22, 2024
AIMS: Echocardiography is a cornerstone in cardiac imaging, and left ventricular (LV) ejection fraction (EF) is a key parameter for patient management. Recent advances in artificial intelligence (AI) have enabled fully automatic measurements of LV vo...
Journal of the American Medical Informatics Association : JAMIA
Feb 16, 2024
OBJECTIVES: We set out to describe academic machine learning (ML) researchers' ethical considerations regarding the development of ML tools intended for use in clinical care.
Journal of bioinformatics and computational biology
Feb 1, 2024
In this paper, we propose a novel approach for predicting the activity/inactivity of molecules with the BRCA1 gene by combining pharmacophore modeling and deep learning techniques. Initially, we generated 3D pharmacophore fingerprints using a pharmac...
Background Deep learning (DL)-accelerated MRI can substantially reduce examination times. However, studies prospectively evaluating the diagnostic performance of DL-accelerated MRI reconstructions in acute suspected stroke are lacking. Purpose To inv...
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