AIMC Topic: Deep Learning

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Deep Learning-Based Framework for Identification of Glioblastoma Tumor using Hyperspectral Images of Human Brain.

Sensors (Basel, Switzerland)
The main goal of brain cancer surgery is to perform an accurate resection of the tumor, preserving as much normal brain tissue as possible for the patient. The development of a non-contact and label-free method to provide reliable support for tumor r...

The Classification of Minor Gait Alterations Using Wearable Sensors and Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper describes how non-invasive wearable sensors can be used in combination with deep learning to classify artificially induced gait alterations without the requirement for a medical professional or gait analyst to be present. This a...

A deep learning approach for real-time detection of sleep spindles.

Journal of neural engineering
OBJECTIVE: Sleep spindles have been implicated in memory consolidation and synaptic plasticity during NREM sleep. Detection accuracy and latency in automatic spindle detection are critical for real-time applications.

DeepChemStable: Chemical Stability Prediction with an Attention-Based Graph Convolution Network.

Journal of chemical information and modeling
In the drug discovery process, unstable compounds in storage can lead to false positive or false negative bioassay conclusions. Prediction of the chemical stability of a compound by de novo methods is complex. Chemical instability prediction is commo...

Imputation of Assay Bioactivity Data Using Deep Learning.

Journal of chemical information and modeling
We describe a novel deep learning neural network method and its application to impute assay pIC values. Unlike conventional machine learning approaches, this method is trained on sparse bioactivity data as input, typical of that found in public and c...

Synthesizing Supervision for Learning Deep Saliency Network without Human Annotation.

IEEE transactions on pattern analysis and machine intelligence
Recently, the research field of salient object detection is undergoing a rapid and remarkable development along with the wide usage of deep neural networks. Being trained with a large number of images annotated with strong pixel-level ground-truth ma...

Deep Learning for Sensor-Based Rehabilitation Exercise Recognition and Evaluation.

Sensors (Basel, Switzerland)
In this paper, a multipath convolutional neural network (MP-CNN) is proposed for rehabilitation exercise recognition using sensor data. It consists of two novel components: a dynamic convolutional neural network (D-CNN) and a state transition probabi...

Explaining the unique nature of individual gait patterns with deep learning.

Scientific reports
Machine learning (ML) techniques such as (deep) artificial neural networks (DNN) are solving very successfully a plethora of tasks and provide new predictive models for complex physical, chemical, biological and social systems. However, in most cases...

Cell Identity Codes: Understanding Cell Identity from Gene Expression Profiles using Deep Neural Networks.

Scientific reports
Understanding cell identity is an important task in many biomedical areas. Expression patterns of specific marker genes have been used to characterize some limited cell types, but exclusive markers are not available for many cell types. A second appr...

The impact of deep learning.

Zeitschrift fur medizinische Physik