AI Medical Compendium Journal:
Journal of medical engineering & technology

Showing 1 to 10 of 36 articles

Deep transfer learning based hierarchical CAD system designs for SFM images.

Journal of medical engineering & technology
Present work involves rigorous experimentation for classification of mammographic masses by employing four deep transfer learning models using hierarchical framework. Experimental work is carried on 518 SFM images of DDSM dataset with 208, 150 and 16...

A combination of deep learning models and type-2 fuzzy for EEG motor imagery classification through spatiotemporal-frequency features.

Journal of medical engineering & technology
Developing a robust and effective technique is crucial for interpreting a user's brainwave signals accurately in the realm of biomedical signal processing. The variability and uncertainty present in EEG patterns over time, compounded by noise, pose n...

An arrhythmia classification using a deep learning and optimisation-based methodology.

Journal of medical engineering & technology
The work proposes a methodology for five different classes of ECG signals. The methodology utilises moving average filter and discrete wavelet transformation for the remove of baseline wandering and powerline interference. The preprocessed signals ar...

Hybrid attention-CNN model for classification of gait abnormalities using EMG scalogram images.

Journal of medical engineering & technology
This research aimed to develop an algorithm for classifying scalogram images generated from electromyography data of patients with Rheumatoid Arthritis and Prolapsed Intervertebral Disc. Electromyography is valuable for assessing muscle function and ...

Comparative study of DCNN and image processing based classification of chest X-rays for identification of COVID-19 patients using fine-tuning.

Journal of medical engineering & technology
The conventional detection of COVID-19 by evaluating the CT scan images is tiresome, often experiences high inter-observer variability and uncertainty issues. This work proposes the automatic detection and classification of COVID-19 by analysing the ...

An enhanced Garter Snake Optimization-assisted deep learning model for lung cancer segmentation and classification using CT images.

Journal of medical engineering & technology
An early detection of lung tumors is critical for better treatment results, and CT scans can reveal lumps in the lungs which are too small to be picked up by conventional X-rays. CT imaging has advantages, but it also exposes a person to radiation fr...

Apnoea detection using ECG signal based on machine learning classifiers and its performances.

Journal of medical engineering & technology
Sleep apnoea is a common disorder affecting sleep quality by obstructing the respiratory airway. This disorder can also be correlated to certain diseases like stroke, depression, neurocognitive disorder, non-communicable disease, etc. We implemented ...

Artificial intelligence and machine learning responses to COVID-19 related inquiries.

Journal of medical engineering & technology
Researchers and scientists can use computational-based models to turn linked data into useful information, aiding in disease diagnosis, examination, and viral containment due to recent artificial intelligence and machine learning breakthroughs. In th...

Enhanced skin burn assessment through transfer learning: a novel framework for human tissue analysis.

Journal of medical engineering & technology
Visual inspection is the typical way for evaluating burns, due to the rising occurrence of burns globally, visual inspection may not be sufficient to detect skin burns because the severity of burns can vary and some burns may not be immediately appar...

Co-design of digital learning resources for care workers: reflections on the neurocare knowhow project.

Journal of medical engineering & technology
Neurocare Knowhow is an online learning platform for care workers who support people with neurological conditions. Care workers often do not receive specialist training around neurological conditions and can experience anxiety and apprehension about ...