AIMC Topic: Algorithms

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Deep Learning-Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors.

JMIR mHealth and uHealth
BACKGROUND: Multimodal wearable technologies have brought forward wide possibilities in human activity recognition, and more specifically personalized monitoring of eating habits. The emerging challenge now is the selection of most discriminative inf...

Segmentation and Classification of Heart Angiographic Images Using Machine Learning Techniques.

Journal of healthcare engineering
Heart angiography is a test in which the concerned medical specialist identifies the abnormality in heart vessels. This type of diagnosis takes a lot of time by the concerned physician. In our proposed method, we segmented the interested regions of h...

HDG-select: A novel GUI based application for gene selection and classification in high dimensional datasets.

PloS one
The selection and classification of genes is essential for the identification of related genes to a specific disease. Developing a user-friendly application with combined statistical rigor and machine learning functionality to help the biomedical res...

Application of deep learning algorithm to detect and visualize vertebral fractures on plain frontal radiographs.

PloS one
BACKGROUND: Identification of vertebral fractures (VFs) is critical for effective secondary fracture prevention owing to their association with the increasing risks of future fractures. Plain abdominal frontal radiographs (PARs) are a common investig...

diSBPred: A machine learning based approach for disulfide bond prediction.

Computational biology and chemistry
The protein disulfide bond is a covalent bond that forms during post-translational modification by the oxidation of a pair of cysteines. In protein, the disulfide bond is the most frequent covalent link between amino acids after the peptide bond. It ...

Machine-Learning Based Determination of Gait Events from Foot-Mounted Inertial Units.

Sensors (Basel, Switzerland)
A promising but still scarcely explored strategy for the estimation of gait parameters based on inertial sensors involves the adoption of machine learning techniques. However, existing approaches are reliable only for specific conditions, inertial me...

Classification of colorectal tissue images from high throughput tissue microarrays by ensemble deep learning methods.

Scientific reports
Tissue microarray (TMA) core images are a treasure trove for artificial intelligence applications. However, a common problem of TMAs is multiple sectioning, which can change the content of the intended tissue core and requires re-labelling. Here, we ...

Disease Concept-Embedding Based on the Self-Supervised Method for Medical Information Extraction from Electronic Health Records and Disease Retrieval: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: The electronic health record (EHR) contains a wealth of medical information. An organized EHR can greatly help doctors treat patients. In some cases, only limited patient information is collected to help doctors make treatment decisions. ...

Involvement of Machine Learning Tools in Healthcare Decision Making.

Journal of healthcare engineering
In the present day, there are many diseases which need to be identified at their early stages to start relevant treatments. If not, they could be uncurable and deadly. Due to this reason, there is a need of analysing complex medical data, medical rep...

Detection of Referable Horizontal Strabismus in Children's Primary Gaze Photographs Using Deep Learning.

Translational vision science & technology
PURPOSE: This study implements and demonstrates a deep learning (DL) approach for screening referable horizontal strabismus based on primary gaze photographs using clinical assessments as a reference. The purpose of this study was to develop and eval...