AIMC Topic: Deep Learning

Clear Filters Showing 28211 to 28220 of 28423 articles

DeepDom: Predicting protein domain boundary from sequence alone using stacked bidirectional LSTM.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
Protein domain boundary prediction is usually an early step to understand protein function and structure. Most of the current computational domain boundary prediction methods suffer from low accuracy and limitation in handling multi-domain types, or ...
Protein Domains Deep Learning Amino Acid Sequence Computational Biology Databases, Protein Neural Networks, Computer Algorithms
View on PubMed

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
The proliferation of healthcare data has brought the opportunities of applying data-driven approaches, such as machine learning methods, to assist diagnosis. Recently, many deep learning methods have been shown with impressive successes in predicting...
Medical Informatics Medical Informatics Computing Humans Deep Learning Medical Informatics Applications Neural Networks, Computer Computational Biology Machine Learning Diagnosis, Computer-Assisted
View on PubMed

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
Electronic phenotyping is the task of ascertaining whether an individual has a medical condition of interest by analyzing their medical record and is foundational in clinical informatics. Increasingly, electronic phenotyping is performed via supervis...
Computational Biology Logistic Models Medical Informatics Electronic Health Records Deep Learning Humans Algorithms Neural Networks, Computer Phenotype Machine Learning Databases, Factual
View on PubMed

Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
Biomedical association studies are increasingly done using clinical concepts, and in particular diagnostic codes from clinical data repositories as phenotypes. Clinical concepts can be represented in a meaningful, vector space using word embedding mo...
Humans Machine Learning Phenotype Databases, Factual Deep Learning Computational Biology International Classification of Diseases Natural Language Processing Medical Informatics Semantics
View on PubMed

Proteomics Analysis of FLT3-ITD Mutation in Acute Myeloid Leukemia Using Deep Learning Neural Network.

Annals of clinical and laboratory science Jan 1, 2019
Deep Learning can significantly benefit cancer proteomics and genomics. In this study, we attempted to determine a set of critical proteins that were associated with the FLT3-ITD mutation in newly-diagnosed acute myeloid leukemia patients. A Deep Lea...
Tandem Repeat Sequences fms-Like Tyrosine Kinase 3 Leukemia, Myeloid, Acute Deep Learning Proteomics Proteome Blood Proteins Mutation Humans Neural Networks, Computer
View on PubMed

Artificial Intelligence and Black-Box Medical Decisions: Accuracy versus Explainability.

The Hastings Center report Jan 1, 2019
Although decision-making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of quest...
Clinical Decision-Making Reproducibility of Results Deep Learning Social Responsibility Knowledge Uncertainty Humans Artificial Intelligence Algorithms
View on PubMed DOI

Deep Learning in Medicine. Are We Ready?

Annals of the Academy of Medicine, Singapore Jan 1, 2019
Machine Learning Melanoma Skin Neoplasms Humans Diabetic Retinopathy Artificial Intelligence Triage Referral and Consultation Deep Learning Image Processing, Computer-Assisted Mass Screening
View on PubMed

Technologies to watch in 2019.

Nature Jan 1, 2019
Humans CRISPR-Cas Systems Synthetic Biology Gene Editing Neural Pathways Cryoelectron Microscopy Single-Cell Analysis Genomics Brain Mapping Animals Deep Learning
View on PubMed DOI

[Potential applications of deep learning-based technologies in Hungarian mammography].

Orvosi hetilap Jan 1, 2019
INTRODUCTION AND AIM: The technology, named 'deep learning' is the promising result of the last two decades of development in computer science. It poses an unavoidable challenge for medicine, how to understand, apply and adopt the - today not fully e...
Mammography Humans Motivation Physician-Patient Relations Artificial Intelligence Hungary Deep Learning User-Computer Interface
View on PubMed DOI

Adverse Drug Events Detection in Clinical Notes by Jointly Modeling Entities and Relations Using Neural Networks.

Drug safety Jan 1, 2019
BACKGROUND AND SIGNIFICANCE: Adverse drug events (ADEs) occur in approximately 2-5% of hospitalized patients, often resulting in poor outcomes or even death. Extraction of ADEs from clinical narratives can accelerate and automate pharmacovigilance. U...
Deep Learning Drug-Related Side Effects and Adverse Reactions Adverse Drug Reaction Reporting Systems Humans Neural Networks, Computer
View on PubMed DOI
Popular Topics
Recent Journals