AIMC Topic: Deep Learning

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Integrating a Multi-label Deep Learning Approach with Protein Information to Compare Bioactive Peptides in Brain and Plasma.

Methods in molecular biology (Clifton, N.J.)
Peptide therapeutics is gaining momentum. Advances in the field of peptidomics have enabled researchers to harvest vital information from various organisms and tissue types concerning peptide existence, expression and function. The development of mas...

Deep Learning-based Thigh Muscle Investigation Using MRI For Prosthetic Development for Patients Undergoing Total Knee Replacement (TKR).

Current medical imaging
BACKGROUND: A prosthetic device is designed based on the quantitative analysis of muscle MRI which will improve the muscle control achieved with functional electrical stimulation/ guided robotic exoskeletons. Electromyography (EMG) provides muscle fu...

The effect of the re-segmentation method on improving the performance of rectal cancer image segmentation models.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Rapid and accurate segmentation of tumor regions from rectal cancer images can better understand the patientâs lesions and surrounding tissues, providing more effective auxiliary diagnostic information. However, cutting rectal tumors with...

Deep learning approaches for breast cancer detection in histopathology images: A review.

Cancer biomarkers : section A of Disease markers
BACKGROUND: Breast cancer is one of the leading causes of death in women worldwide. Histopathology analysis of breast tissue is an essential tool for diagnosing and staging breast cancer. In recent years, there has been a significant increase in rese...

Design and Development of Hypertuned Deep learning Frameworks for Detection and Severity Grading of Brain Tumor using Medical Brain MR images.

Current medical imaging
BACKGROUND: Brain tumor is a grave illness causing worldwide fatalities. The current detection methods for brain tumors are manual, invasive, and rely on histopathological analysis. Determining the type of brain tumor after its detection relies on bi...

A novel measurement approach to dynamic change of limb length discrepancy using deep learning and wearable sensors.

Science progress
The accurate identification of dynamic change of limb length discrepancy (LLD) in non-clinical settings is of great significance for monitoring gait function change in people's everyday lives. How to search for advanced techniques to measure LLD chan...

Neural Computation-Based Methods for the Early Diagnosis and Prognosis of Alzheimer's Disease Not Using Neuroimaging Biomarkers: A Systematic Review.

Journal of Alzheimer's disease : JAD
BACKGROUND: The growing number of older adults in recent decades has led to more prevalent geriatric diseases, such as strokes and dementia. Therefore, Alzheimer's disease (AD), as the most common type of dementia, has become more frequent too.

Promoting Physical Activity Among Workers for Better Mental Health: An mHealth Intervention With Deep Learning.

Journal of UOEH
There is clear scientific evidence that physical activity helps to prevent depression and anxiety. Utilizing mobile health (mHealth) technologies to enable physical activity is promising, but the evidence of the effectiveness of mHealth interventions...

Deep Learning of Cancer Stem Cell Morphology.

Methods in molecular biology (Clifton, N.J.)
Knowledge regarding cancer stem cell (CSC) morphology is limited, and more extensive studies are therefore required. Image recognition technologies using artificial intelligence (AI) require no previous expertise in image annotation. Herein, we descr...

VGG19 demonstrates the highest accuracy rate in a nine-class wound classification task among various deep learning networks: a pilot study.

Wounds : a compendium of clinical research and practice
BACKGROUND: Current literature suggests relatively low accuracy of multi-class wound classification tasks using deep learning networks. Solutions are needed to address the increasing diagnostic burden of wounds on wound care professionals and to aid ...