AIMC Topic: Deep Learning

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Benefits of deep learning for delineation of organs at risk in head and neck cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE/OBJECTIVE: Precise delineation of organs at risk (OARs) in head and neck cancer (HNC) is necessary for accurate radiotherapy. Although guidelines exist, significant interobserver variability (IOV) remains. The aim was to validate a 3D convolu...

Prognosis of cervical myelopathy based on diffusion tensor imaging with artificial intelligence methods.

NMR in biomedicine
Diffusion tensor imaging (DTI) has been proposed for the prognosis of cervical myelopathy (CM), but the manual analysis of DTI features is complicated and time consuming. This study evaluated the potential of artificial intelligence (AI) methods in t...

Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.

Nature methods
In mass-spectrometry-based proteomics, the identification and quantification of peptides and proteins heavily rely on sequence database searching or spectral library matching. The lack of accurate predictive models for fragment ion intensities impair...

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk.

Nature genetics
We address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts the specific regulatory effects and the deleterious impact of genetic variants. Applying this framework to 1,7...

Deep transfer learning methods for colon cancer classification in confocal laser microscopy images.

International journal of computer assisted radiology and surgery
PURPOSE: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For feedback during interventions, real-time in vivo imaging with confocal laser microscopy has been propos...

An empirical evaluation of deep learning for ICD-9 code assignment using MIMIC-III clinical notes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Code assignment is of paramount importance in many levels in modern hospitals, from ensuring accurate billing process to creating a valid record of patient care history. However, the coding process is tedious and subjective,...

The Deep Learning-Based Recommender System "Pubmender" for Choosing a Biomedical Publication Venue: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: It is of great importance for researchers to publish research results in high-quality journals. However, it is often challenging to choose the most suitable publication venue, given the exponential growth of journals and conferences. Alth...

Brain ventricle parcellation using a deep neural network: Application to patients with ventriculomegaly.

NeuroImage. Clinical
Numerous brain disorders are associated with ventriculomegaly, including both neuro-degenerative diseases and cerebrospinal fluid disorders. Detailed evaluation of the ventricular system is important for these conditions to help understand the pathog...

Categorization of free-text drug orders using character-level recurrent neural networks.

International journal of medical informatics
BACKGROUND AND PURPOSE: Manual annotation and categorization of non-standardized text ("free-text") of drug orders entered into electronic health records is a labor-intensive task. However, standardization is required for drug order analyses and has ...

Extraction of the cardiac waveform from simultaneous multislice fMRI data using slice sorted averaging and a deep learning reconstruction filter.

NeuroImage
Cardiac signal contamination has long confounded the analysis of blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI). Cardiac pulsation results in significant BOLD signal changes, especially in and around blood vesse...