AIMC Topic: Algorithms

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Wearable IMU-Based Human Activity Recognition Algorithm for Clinical Balance Assessment Using 1D-CNN and GRU Ensemble Model.

Sensors (Basel, Switzerland)
In this study, a wearable inertial measurement unit system was introduced to assess patients via the Berg balance scale (BBS), a clinical test for balance assessment. For this purpose, an automatic scoring algorithm was developed. The principal aim o...

Prioritisation Assessment and Robust Predictive System for Medical Equipment: A Comprehensive Strategic Maintenance Management.

Frontiers in public health
The advancement of technology in medical equipment has significantly improved healthcare services. However, failures in upkeeping reliability, availability, and safety affect the healthcare services quality and significant impact can be observed in o...

Development and validation of a supervised deep learning algorithm for automated whole-slide programmed death-ligand 1 tumour proportion score assessment in non-small cell lung cancer.

Histopathology
AIMS: Immunohistochemical programmed death-ligand 1 (PD-L1) staining to predict responsiveness to immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) has several drawbacks: a robust gold standard is lacking, and there is substa...

An inertial neural network approach for robust time-of-arrival localization considering clock asynchronization.

Neural networks : the official journal of the International Neural Network Society
This paper presents an inertial neural network to solve the source localization optimization problem with l-norm objective function based on the time of arrival (TOA) localization technique. The convergence and stability of the inertial neural networ...

Open-source deep learning-based automatic segmentation of mouse Schlemm's canal in optical coherence tomography images.

Experimental eye research
The purpose of this study was to develop an automatic deep learning-based approach and corresponding free, open-source software to perform segmentation of the Schlemm's canal (SC) lumen in optical coherence tomography (OCT) scans of living mouse eyes...

Analysis of Gastrointestinal Acoustic Activity Using Deep Neural Networks.

Sensors (Basel, Switzerland)
Automated bowel sound (BS) analysis methods were already well developed by the early 2000s. Accuracy of ~90% had been achieved by several teams using various analytical approaches. Clinical research on BS had revealed their high potential in the non-...

Drug knowledge discovery via multi-task learning and pre-trained models.

BMC medical informatics and decision making
BACKGROUND: Drug repurposing is to find new indications of approved drugs, which is essential for investigating new uses for approved or investigational drug efficiency. The active gene annotation corpus (named AGAC) is annotated by human experts, wh...

Mental Health Monitoring Based on Multiperception Intelligent Wearable Devices.

Contrast media & molecular imaging
In order to improve the accuracy of the evaluation results of multiperception intelligent wearable devices, the mathematical statistical characteristics based on speech, behavior, environment, and physical signs are proposed; first, the PCA feature c...

Medical and Health Data Classification Method Based on Machine Learning.

Journal of healthcare engineering
The information defined in medical health data is researched based on machine learning-related algorithms. Also, this paper used random forest and other related algorithms to perform health data training and fitting. Research shows that the algorithm...

Keratoconus Severity Classification Using Features Selection and Machine Learning Algorithms.

Computational and mathematical methods in medicine
Keratoconus is a noninflammatory disease characterized by thinning and bulging of the cornea, generally appearing during adolescence and slowly progressing, causing vision impairment. However, the detection of keratoconus remains difficult in the ear...