AIMC Topic: Deep Learning

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GPS-Palm: a deep learning-based graphic presentation system for the prediction of S-palmitoylation sites in proteins.

Briefings in bioinformatics Mar 22, 2021
As an important reversible lipid modification, S-palmitoylation mainly occurs at specific cysteine residues in proteins, participates in regulating various biological processes and is associated with human diseases. Besides experimental assays, compu...
Lipoylation Proteins Computer Graphics Algorithms Animals Humans Mice Deep Learning Software Computational Biology
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DeepCPP: a deep neural network based on nucleotide bias information and minimum distribution similarity feature selection for RNA coding potential prediction.

Briefings in bioinformatics Mar 22, 2021
The development of deep sequencing technologies has led to the discovery of novel transcripts. Many in silico methods have been developed to assess the coding potential of these transcripts to further investigate their functions. Existing methods per...
Humans Neural Networks, Computer RNA, Messenger RNA, Long Noncoding Open Reading Frames Animals Deep Learning
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Importance-aware personalized learning for early risk prediction using static and dynamic health data.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: Accurate risk prediction is important for evaluating early medical treatment effects and improving health care quality. Existing methods are usually designed for dynamic medical data, which require long-term observations. Meanwhile, import...
Humans Neural Networks, Computer Data Mining Datasets as Topic Peptic Ulcer Hemorrhage Deep Learning Risk Assessment Precision Medicine Models, Theoretical Prognosis
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STAN: spatio-temporal attention network for pandemic prediction using real-world evidence.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: We aim to develop a hybrid model for earlier and more accurate predictions for the number of infected cases in pandemics by (1) using patients' claims data from different counties and states that capture local disease status and medical re...
Models, Statistical Epidemiologic Methods Deep Learning Humans United States Neural Networks, Computer Pandemics COVID-19
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On collaborative reinforcement learning to optimize the redistribution of critical medical supplies throughout the COVID-19 pandemic.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: This work investigates how reinforcement learning and deep learning models can facilitate the near-optimal redistribution of medical equipment in order to bolster public health responses to future crises similar to the COVID-19 pandemic.
Equipment and Supplies Resource Allocation Algorithms Deep Learning Public Health Administration Pandemics COVID-19 Machine Learning
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Discovery of Ongoing Selective Sweeps within Anopheles Mosquito Populations Using Deep Learning.

Molecular biology and evolution Mar 9, 2021
Identification of partial sweeps, which include both hard and soft sweeps that have not currently reached fixation, provides crucial information about ongoing evolutionary responses. To this end, we introduce partialS/HIC, a deep learning method to d...
Deep Learning Selection, Genetic Insecticide Resistance Animals Genome, Insect Anopheles
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Deep learning formulation of electrocardiographic imaging integrating image and signal information with data-driven regularization.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Mar 4, 2021
AIMS: Electrocardiographic imaging (ECGI) is a promising tool to map the electrical activity of the heart non-invasively using body surface potentials (BSP). However, it is still challenging due to the mathematically ill-posed nature of the inverse p...
Artificial Intelligence Heart Deep Learning Electrocardiography Body Surface Potential Mapping Humans
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Sequence representation approaches for sequence-based protein prediction tasks that use deep learning.

Briefings in functional genomics Mar 2, 2021
Deep learning has been increasingly used in bioinformatics, especially in sequence-based protein prediction tasks, as large amounts of biological data are available and deep learning techniques have been developed rapidly in recent years. For sequenc...
Computational Biology Proteins Amino Acid Sequence Neural Networks, Computer Deep Learning
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[A Preliminary Study of Applying Geometric Deep Learning in Brain Morphometry for Diagnosis of Alzheimer's Disease].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition Mar 1, 2021
OBJECTIVE: A predictive model of Alzheimer's disease (AD) was established based on brain surface meshes and geometric deep learning, and its performance was evaluated.
Deep Learning Brain Magnetic Resonance Imaging Aged Alzheimer Disease Humans Neural Networks, Computer
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[Noise Reduction Effect of Deep-learning-based Image Reconstruction Algorithms in Thin-section Chest CT].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition Mar 1, 2021
OBJECTIVE: To evaluate the noise reduction effect of deep learning-based reconstruction algorithms in thin-section chest CT images by analyzing images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (A...
Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Deep Learning Humans Radiation Dosage Algorithms
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