AIMC Topic: Deep Learning

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Influence of Deep Learning Based Image Reconstruction on Quantitative Results of Coronary Artery Calcium Scoring.

Academic radiology
RATIONALE AND OBJECTIVES: To assess the impact of deep learning-based imaging reconstruction (DLIR) on quantitative results of coronary artery calcium scoring (CACS) and to evaluate the potential of DLIR for radiation dose reduction in CACS.

Applications of Artificial Intelligence, Machine Learning, and Deep Learning in Nutrition: A Systematic Review.

Nutrients
In industry 4.0, where the automation and digitalization of entities and processes are fundamental, artificial intelligence (AI) is increasingly becoming a pivotal tool offering innovative solutions in various domains. In this context, nutrition, a c...

Fully automated deep learning approach to dental development assessment in panoramic radiographs.

BMC oral health
BACKGROUND: Dental development assessment is an important factor in dental age estimation and dental maturity evaluation. This study aimed to develop and evaluate the performance of an automated dental development staging system based on Demirjian's ...

Development of a Deep Learning System for Intraoperative Identification of Cancer Metastases.

Annals of surgery
OBJECTIVE: The aim of this study was to develop and test a prototype of a deep learning surgical guidance system [computer-assisted staging laparoscopy (CASL)] that can intraoperative identify peritoneal surface metastases on routine laparoscopy imag...

Performance Evaluation of Deep, Shallow and Ensemble Machine Learning Methods for the Automated Classification of Alzheimer's Disease.

International journal of neural systems
Artificial intelligence (AI)-based approaches are crucial in computer-aided diagnosis (CAD) for various medical applications. Their ability to quickly and accurately learn from complex data is remarkable. Deep learning (DL) models have shown promisin...

Automated detection of myocardial infarction based on an improved state refinement module for LSTM/GRU.

Artificial intelligence in medicine
Myocardial infarction (MI) is a common cardiovascular disease caused by the blockages of coronary arteries. The visual inspection of electrocardiogram (ECG) is the main diagnosis pattern, while it is taxing and time-consuming. Motivated from state re...

Advancing Drug-Target Interaction prediction with BERT and subsequence embedding.

Computational biology and chemistry
Exploring the relationship between proteins and drugs plays a significant role in discovering new synthetic drugs. The Drug-Target Interaction (DTI) prediction is a fundamental task in the relationship between proteins and drugs. Unlike encoding prot...

Deep learning denoising reconstruction enables faster T2-weighted FLAIR sequence acquisition with satisfactory image quality.

Journal of medical imaging and radiation oncology
INTRODUCTION: Deep learning reconstruction (DLR) technologies are the latest methods attempting to solve the enduring problem of reducing MRI acquisition times without compromising image quality. The clinical utility of this reconstruction technique ...

Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening.

Accounts of chemical research
Molecular docking, also termed ligand docking (LD), is a pivotal element of structure-based virtual screening (SBVS) used to predict the binding conformations and affinities of protein-ligand complexes. Traditional LD methodologies rely on a search a...

Brain-machine interface based on deep learning to control asynchronously a lower-limb robotic exoskeleton: a case-of-study.

Journal of neuroengineering and rehabilitation
BACKGROUND: This research focused on the development of a motor imagery (MI) based brain-machine interface (BMI) using deep learning algorithms to control a lower-limb robotic exoskeleton. The study aimed to overcome the limitations of traditional BM...