AIMC Topic: Databases, Factual

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Short Single-Lead ECG Signal Delineation-Based Deep Learning: Implementation in Automatic Atrial Fibrillation Identification.

Sensors (Basel, Switzerland)
Physicians manually interpret an electrocardiogram (ECG) signal morphology in routine clinical practice. This activity is a monotonous and abstract task that relies on the experience of understanding ECG waveform meaning, including P-wave, QRS-comple...

Classification of Ear Imagery Database using Bayesian Optimization based on CNN-LSTM Architecture.

Journal of digital imaging
The external and middle ear conditions are diagnosed using a digital otoscope. The clinical diagnosis of ear conditions is suffered from restricted accuracy due to the increased dependency on otolaryngologist expertise, patient complaint, blurring of...

DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues.

Journal of chemical information and modeling
In this paper, we present a deep learning algorithm for automated design of druglike analogues (DeLA-Drug), a recurrent neural network (RNN) model composed of two long short-term memory (LSTM) layers and conceived for data-driven generation of simila...

No-Reference Video Quality Assessment Using Multi-Pooled, Saliency Weighted Deep Features and Decision Fusion.

Sensors (Basel, Switzerland)
With the constantly growing popularity of video-based services and applications, no-reference video quality assessment (NR-VQA) has become a very hot research topic. Over the years, many different approaches have been introduced in the literature to ...

Identification of data elements for blood gas analysis dataset: a base for developing registries and artificial intelligence-based systems.

BMC health services research
BACKGROUND: One of the challenging decision-making tasks in healthcare centers is the interpretation of blood gas tests. One of the most effective assisting approaches for the interpretation of blood gas analysis (BGA) can be artificial intelligence ...

Recurrent neural network to predict hyperelastic constitutive behaviors of the skeletal muscle.

Medical & biological engineering & computing
Hyperelastic constitutive laws have been commonly used to model the passive behavior of the human skeletal muscle. Despite many efforts, the use of accurate finite element formulations of hyperelastic constitutive laws is still time-consuming for a r...

Compound-protein interaction prediction by deep learning: Databases, descriptors and models.

Drug discovery today
The screening of compound-protein interactions (CPIs) is one of the most crucial steps in finding hit and lead compounds. Deep learning (DL) methods for CPI prediction can address intrinsic limitations of traditional HTS and virtual screening with th...

Systematic Review and Comparison of Publicly Available ICU Data Sets-A Decision Guide for Clinicians and Data Scientists.

Critical care medicine
OBJECTIVE: As data science and artificial intelligence continue to rapidly gain traction, the publication of freely available ICU datasets has become invaluable to propel data-driven clinical research. In this guide for clinicians and researchers, we...

CateCom: A Practical Data-Centric Approach to Categorization of Computational Models.

Journal of chemical information and modeling
The advent of data-driven science in the 21st century brought about the need for well-organized structured data and associated infrastructure able to facilitate the applications of artificial intelligence and machine learning. We present an effort ai...

Brain Decoding Using fMRI Images for Multiple Subjects through Deep Learning.

Computational and mathematical methods in medicine
Substantial information related to human cerebral conditions can be decoded through various noninvasive evaluating techniques like fMRI. Exploration of the neuronal activity of the human brain can divulge the thoughts of a person like what the subjec...