AIMC Topic: Deep Learning

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Predicting multipotency of human adult stem cells derived from various donors through deep learning.

Scientific reports
Adult stem cell-based therapeutic approaches have great potential in regenerative medicine because of their immunoregulatory properties and multidifferentiation capacity. Nevertheless, the outcomes of stem cell‑based therapies to date have shown inco...

Evaluation of deep learning models in contactless human motion detection system for next generation healthcare.

Scientific reports
Recent decades have witnessed the growing importance of human motion detection systems based on artificial intelligence (AI). The growing interest in human motion detection systems is the advantages of automation in the monitoring of patients remotel...

Automatic assessment of knee osteoarthritis severity in portable devices based on deep learning.

Journal of orthopaedic surgery and research
BACKGROUND: For knee osteoarthritis, the commonly used radiology severity criteria Kellgren-Lawrence lead to variability among surgeons. Most existing diagnosis models require preprocessed radiographs and specific equipment.

Feedback-AVPGAN: Feedback-guided generative adversarial network for generating antiviral peptides.

Journal of bioinformatics and computational biology
In this study, we propose , a system that aims to computationally generate novel antiviral peptides (AVPs). This system relies on the key premise of the Generative Adversarial Network (GAN) model and the Feedback method. GAN, a generative modeling ap...

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.

Genomics, proteomics & bioinformatics
Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to quantify the gene expression profile of thousands of single cells simultaneously. Analysis of scRNA-seq data plays an important role in the study of cell states and pheno...

Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study.

European radiology
OBJECTIVES: Accurate detection of carotid plaque using ultrasound (US) is essential for preventing stroke. However, the diagnostic performance of junior radiologists (with approximately 1 year of experience in carotid US evaluation) is relatively poo...

Accuracy of a Deep Learning Method for Heart Sound Analysis is Unrealistic.

Neural networks : the official journal of the International Neural Network Society

Deep Learning-Enhanced Potentiometric Aptasensing with Magneto-Controlled Sensors.

Angewandte Chemie (International ed. in English)
Bioelectronic sensors that report charge changes of a biomolecule upon target binding enable direct and sensitive analyte detection but remain a major challenge for potentiometric measurement, mainly due to Debye Length limitations and the need for m...

Heart disease prediction using IoT based framework and improved deep learning approach: Medical application.

Medical engineering & physics
Heart disease is the biggest cause of death in the globe. The method of predicting cardiac disease is exceedingly complex. It can only be done properly if the doctor has a lot of expertise and is well-versed in the condition. IoT-based illness predic...