AIMC Topic: Deep Learning

Clear Filters Showing 28261 to 28270 of 28423 articles

Development and evaluation of a deep learning model for protein-ligand binding affinity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Structure based ligand discovery is one of the most successful approaches for augmenting the drug discovery process. Currently, there is a notable shift towards machine learning (ML) methodologies to aid such procedures. Deep learning has...

Fully Automated Echocardiogram Interpretation in Clinical Practice.

Circulation
BACKGROUND: Automated cardiac image interpretation has the potential to transform clinical practice in multiple ways, including enabling serial assessment of cardiac function by nonexperts in primary care and rural settings. We hypothesized that adva...

YAMDA: thousandfold speedup of EM-based motif discovery using deep learning libraries and GPU.

Bioinformatics (Oxford, England)
MOTIVATION: Motif discovery in large biopolymer sequence datasets can be computationally demanding, presenting significant challenges for discovery in omics research. MEME, arguably one of the most popular motif discovery software, takes quadratic ti...

Perspectives on Machine Learning for Classification of Schizotypy Using fMRI Data.

Schizophrenia bulletin
Functional magnetic resonance imaging is capable of estimating functional activation and connectivity in the human brain, and lately there has been increased interest in the use of these functional modalities combined with machine learning for identi...

Protein secondary structure prediction improved by recurrent neural networks integrated with two-dimensional convolutional neural networks.

Journal of bioinformatics and computational biology
Protein secondary structure prediction (PSSP) is an important research field in bioinformatics. The representation of protein sequence features could be treated as a matrix, which includes the amino-acid residue (time-step) dimension and the feature ...

Identifying patients with familial hypercholesterolemia using data mining methods in the Northern Great Plain region of Hungary.

Atherosclerosis
BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is one of the most frequent diseases with monogenic inheritance. Previous data indicated that the heterozygous form occurred in 1:250 people. Based on these reports, around 36,000-40,000 people ...

3D deep learning for detecting pulmonary nodules in CT scans.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To demonstrate and test the validity of a novel deep-learning-based system for the automated detection of pulmonary nodules.

Deep Learning-Based Computer-Aided Diagnosis System for Localization and Diagnosis of Metastatic Lymph Nodes on Ultrasound: A Pilot Study.

Thyroid : official journal of the American Thyroid Association
BACKGROUND: The presence of metastatic lymph nodes is a prognostic indicator for patients with thyroid carcinomas and is an important determinant of clinical decision making. However, evaluating neck lymph nodes requires experience and is labor- and ...

[Big data and deep learning in preventive and rehabilitation medicine].

Der Orthopade
The digitalization in medicine has led to almost universal availability of information to different healthcare professionals and accelerated clinical pathways. Fast-track concepts and short hospital stays require intelligent and practicable systems i...