AIMC Topic: Neural Networks, Computer

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Efficient implementation of convolutional neural networks in the data processing of two-photon in vivo imaging.

Bioinformatics (Oxford, England)
MOTIVATION: Functional imaging at single-neuron resolution offers a highly efficient tool for studying the functional connectomics in the brain. However, mainstream neuron-detection methods focus on either the morphologies or activities of neurons, w...

Prediction of amyloid aggregation rates by machine learning and feature selection.

The Journal of chemical physics
A novel data-based machine learning algorithm for predicting amyloid aggregation rates is reported in this paper. Based on a highly nonlinear projection from 16 intrinsic features of a protein and 4 extrinsic features of the environment to the protei...

[Research progress and challenges of deep learning in medical image registration].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
With the development of image-guided surgery and radiotherapy, the demand for medical image registration is stronger and the challenge is greater. In recent years, deep learning, especially deep convolution neural networks, has made excellent achieve...

Relationship Between Very Cold Outside Weather and Surgical Outcome: Integrating Shallow and Deep Artificial Neural Nets.

Studies in health technology and informatics
Patients' hospital length of stay (LOS) as a surgical outcome is important indicator of quality of care. We used EMR data to build artificial neural network models to better understand the impact of cold weather on outcome of first surgeries in a day...

An Approach of Integrating Domain Knowledge into Data-Driven Diagnostic Model.

Studies in health technology and informatics
A diagnostic model of general diseases could help general practitioners to decrease misdiagnoses and reduce workload. In this paper, we developed a neural network model that can classify potential diagnoses among 100 selected common diseases based on...

Prediction of Clinical Events in Hemodialysis Patients Using an Artificial Neural Network.

Studies in health technology and informatics
Advanced chronic kidney disease (CKD) requires routine renal replacement therapy (RRT) that involves hemodialysis (HD) which may cause increased risk of muscle spasms, cardiovascular events, and death. We used Artificial Neural Network (ANN) method t...

Extracting Symptom Names and Disease-Symptom Relationships from Web Texts Using a Multi-Column Convolutional Neural Network.

Studies in health technology and informatics
We propose a method to create large-scale Japanese medical dictionaries that include symptom names and information about the relationship between a disease and its symptoms using a large web archive that includes large amounts of text written by non-...

Validating Auto-Suggested Changes for SNOMED CT in Non-Lattice Subgraphs Using Relational Machine Learning.

Studies in health technology and informatics
An attractive feature of non-lattice-based ontology auditing methods is its ability to not only identify potential quality issues, but also automatically generate the corresponding fixes. However, exhaustive manual evaluation of the validity of sugge...

Improving the Prescription Process Information Support with Structured Medical Prospectuses Using Neural Networks.

Studies in health technology and informatics
To provide the best treatment, a physician needs information about both the patient and the medicines matching the patient status and improving it. In this article, we present three methods for structuring the sections of medical prospectuses using n...

Recurrent Deep Network Models for Clinical NLP Tasks: Use Case with Sentence Boundary Disambiguation.

Studies in health technology and informatics
Although a number of foundational natural language processing (NLP) tasks like text segmentation are considered a simple problem in the general English domain dominated by well-formed text, complexities of clinical documentation lead to poor performa...