AIMC Topic: Humans

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Role of deep learning in brain tumor detection and classification (2015 to 2020): A review.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
During the last decade, computer vision and machine learning have revolutionized the world in every way possible. Deep Learning is a sub field of machine learning that has shown remarkable results in every field especially biomedical field due to its...

Effects of gait training with a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), on quality of life in patients with neuromuscular disease, able to walk independently with aids.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Robot-assisted gait training using a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), has been shown to improve the mobility of patients with neurological disorders; however, its effect on the quality of life (QOL) of patients is not cl...

Dual energy CT image prediction on primary tumor of lung cancer for nodal metastasis using deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Lymph node metastasis (LNM) identification is the most clinically important tasks related to survival and recurrence from lung cancer. However, the preoperative prediction of nodal metastasis remains a challenge to determine surgical plans and pretre...

Comparison of texture-based classification and deep learning for plantar soft tissue histology segmentation.

Computers in biology and medicine
Histomorphological measurements can be used to identify microstructural changes related to disease pathomechanics, in particular, plantar soft tissue changes with diabetes. However, these measurements are time-consuming and susceptible to sampling an...

Assessing the speed-accuracy trade-offs of popular convolutional neural networks for single-crop rib fracture classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Rib fractures are injuries commonly assessed in trauma wards. Deep learning has demonstrated state-of-the-art accuracy for a variety of tasks, including image classification. This paper assesses the speed-accuracy trade-offs and general suitability o...

Exploring the relationship between the dielectric properties and viability of human normal hepatic tissues from 10 Hz to 100 MHz based on grey relational analysis and BP neural network.

Computers in biology and medicine
Liver is an important parenchyma organ, and its tissue viability plays an important role in liver transplantation and liver ischemic injury assessment. Dielectric property is a useful biophysical feature that provides insights into the structure and ...

Non-Contact Respiration Measurement Method Based on RGB Camera Using 1D Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Conventional respiration measurement requires a separate device and/or can cause discomfort, so it is difficult to perform routinely, even for patients with respiratory diseases. The development of contactless respiration measurement technology would...

Breast cancer risk prediction in African women using Random Forest Classifier.

Cancer treatment and research communications
INTRODUCTION: One of the most important steps in combating breast cancer is early and accurate diagnosis. Unfortunately, breast cancer is asymptomatic at the early stage, although some symptoms are presented at a later time, but at symptomatic stage ...

Randomised controlled trials in medical AI: ethical considerations.

Journal of medical ethics
In recent years, there has been a surge of high-profile publications on applications of artificial intelligence (AI) systems for medical diagnosis and prognosis. While AI provides various opportunities for medical practice, there is an emerging conse...

Learning to recognize while learning to speak: Self-supervision and developing a speaking motor.

Neural networks : the official journal of the International Neural Network Society
Traditionally, learning speech synthesis and speech recognition were investigated as two separate tasks. This separation hinders incremental development for concurrent synthesis and recognition, where partially-learned synthesis and partially-learned...