AIMC Topic: Reproducibility of Results

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A SYSTEMATIC REVIEW OF DEEP LEARNING APPLICATIONS FOR OPTICAL COHERENCE TOMOGRAPHY IN AGE-RELATED MACULAR DEGENERATION.

Retina (Philadelphia, Pa.)
PURPOSE: To survey the current literature regarding applications of deep learning to optical coherence tomography in age-related macular degeneration (AMD).

Best practice and reproducible science are required to advance artificial intelligence in real-world applications.

Briefings in bioinformatics
Drug-induced liver injury (DILI) is one of the most significant concerns in medical practice but yet it still cannot be fully recapitulated with existing in vivo, in vitro and in silico approaches. To address this challenge, Chen et al. [ 1] develope...

BayeshERG: a robust, reliable and interpretable deep learning model for predicting hERG channel blockers.

Briefings in bioinformatics
Unintended inhibition of the human ether-à-go-go-related gene (hERG) ion channel by small molecules leads to severe cardiotoxicity. Thus, hERG channel blockage is a significant concern in the development of new drugs. Several computational models hav...

Stressalyzer: Convolutional Neural Network Framework for Personalized Stress Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Stress detection and monitoring is an active area of research with important implications for an individual's personal, professional, and social health. Current approaches for stress classification use traditional machine learning algorithms trained ...

A Practical Post-Stroke Elbow Spasticity Assessment Using an Upper Limb Rehabilitation Robot: A Validation Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Spasticity is a motor disorder characterised by a velocity-dependent increase in muscle tone, which is critical in neurorehabilitation given its high prevalence and potential negative influence among the post-stroke population. Accurate measurement o...

Stress Detection from Surface Electromyography using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The study of stress and its implications has been the focus of interest in various fields of science. Many automated/semi-automated stress detection systems based on physiological markers have been gaining enormous popularity and importance in recent...

[Various Considerations on Robot-assisted Cardiac Surgery].

Kyobu geka. The Japanese journal of thoracic surgery
Robot-assisted cardiac surgery offers the most minimally-invasive approach to the surgical treatment of valvular heart disease and coronary artery disease. However, robot-assisted cardiac surgery is still far from being a standardized operation. We b...

Conception, Development and Validation of Classification Methods for Coding Support of Rare Diseases Using Artificial Intelligence.

Studies in health technology and informatics
Automated coding of diseases can support hospitals in the billing of inpatient cases with the health insurance funds. This paper describes the implementation and evaluation of classification methods for two selected Rare Diseases. Different classifie...

A Novel Early Warning Model for Hand, Foot and Mouth Disease Prediction Based on a Graph Convolutional Network.

Biomedical and environmental sciences : BES
OBJECTIVES: Hand, foot and mouth disease (HFMD) is a widespread infectious disease that causes a significant disease burden on society. To achieve early intervention and to prevent outbreaks of disease, we propose a novel warning model that can accur...