AIMC Topic: Deep Learning

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Application of artificial intelligence for the classification of the clinical outcome and therapy in patients with viral infections: The case of COVID-19.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: With the end of the coronavirus disease 2019 (COVID-19) pandemic, it becomes intriguing to observe the impact of innovative digital technologies on the diagnosis and management of diseases, in order to improve clinical outcomes for patien...

Deep Learning for Predicting Gene Regulatory Networks: A Step-by-Step Protocol in R.

Methods in molecular biology (Clifton, N.J.)
Deep learning has emerged as a powerful tool for solving complex problems, including reconstruction of gene regulatory networks within the realm of biology. These networks consist of transcription factors and their associations with genes they regula...

Deep-learning model for prenatal congenital heart disease screening generalizes to community setting and outperforms clinical detection.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVES: Despite nearly universal prenatal ultrasound screening programs, congenital heart defects (CHD) are still missed, which may result in severe morbidity or even death. Deep machine learning (DL) can automate image recognition from ultrasoun...

Comparative study of the glistening between four intraocular lens models assessed by OCT and deep learning.

Journal of cataract and refractive surgery
PURPOSE: To evaluate the glistening in 4 different models of intraocular lenses (IOLs) using optical coherence tomography (OCT) and deep learning (DL).

Recent Deep Learning Applications to Structure-Based Drug Design.

Methods in molecular biology (Clifton, N.J.)
Identification and optimization of small molecules that bind to and modulate protein function is a crucial step in the early stages of drug development. For decades, this process has benefitted greatly from the use of computational models that can pr...

Implementation and Efficient Analysis of Preprocessing Techniques in Deep Learning for Image Classification.

Current medical imaging
BACKGROUND: Deep learning models have recently been preferred to perform certain image-processing tasks. Recently, with the increasing radiation, heat, and poor lighting conditions, the raw image samples may contain noisy and ambiguous information.

An Early Detection and Classification of Alzheimer's Disease Framework Based on ResNet-50.

Current medical imaging
OBJECTIVE: The objective of this study is to develop a more effective early detection system for Alzheimer's disease (AD) using a Deep Residual Network (ResNet) model by addressing the issue of convolutional layers in conventional Convolutional Neura...

Retraction to: “Performance Analysis of Alexnet for Classification of Knee Osteoarthritis.

Current medical imaging
UNLABELLED: It has come to the publisher’s attention that the article is a duplication of a published paper in another journal, NeuroQuantology, available at the following link: https://neuroquantology.com/media/article_pdfs/1686-1692.pdf This raises...

Learning technology for detection and grading of cancer tissue using tumour ultrasound images1.

Journal of X-ray science and technology
BACKGROUND: Early diagnosis of breast cancer is crucial to perform effective therapy. Many medical imaging modalities including MRI, CT, and ultrasound are used to diagnose cancer.

Deep learning based decision tree ensembles for incomplete medical datasets.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: In practice, the collected datasets for data analysis are usually incomplete as some data contain missing attribute values. Many related works focus on constructing specific models to produce estimations to replace the missing values, to ...