Diagnosis of cerebral microbleed via VGG and extreme learning machine trained by Gaussian map bat algorithm.

Cerebral microbleed (CMB) is a serious public health concern. It is associated with dementia, which can be detected with brain magnetic resonance image (MRI). CMBs often appear as tiny round dots on MRIs, and they can be spotted anywhere over brain.

Multiclass Convolution Neural Network for Classification of COVID-19 CT Images.

In the late December of 2019, a novel coronavirus was discovered in Wuhan, China. In March 2020, WHO announced this epidemic had become a global pandemic and that the novel coronavirus may be mild to most people. However, some people may experience a severe illness that results in hospitalization or maybe death.

The Promise for Reducing Healthcare Cost with Predictive Model: An Analysis with Quantized Evaluation Metric on Readmission.

Quality of care data has gained transparency captured through various measurements and reporting. Readmission measure is especially related to unfavorable patient outcomes that directly bends the curve of healthcare cost. Under the Hospital Readmission Reduction Program, payments to hospitals were reduced for those with excessive 30-day rehospitalization rates.

Hippocampus Segmentation Method Based on Subspace Patch-Sparsity Clustering in Noisy Brain MRI.

Since the hippocampus is of small size, low contrast, and irregular shape, a novel hippocampus segmentation method based on subspace patch-sparsity clustering in brain MRI is proposed to improve the segmentation accuracy, which requires that the representation coefficients in different subspaces should be as sparse as possible, while the representation coefficients in the same subspace should be as average as possible. By restraining the coefficient matrix with the patch-sparse constraint, the coefficient matrix contains a patch-sparse structure, which is helpful to the hippocampus segmentation. The experimental results show that our proposed method is effective in the noisy brain MRI data, which can well deal with hippocampus segmentation problem.

5G Edge Computing Enabled Directional Data Collection for Medical Community Electronic Health Records.

It is important to promote the development and application of hospital information system, community health service system, etc. However, it is difficult to realize the intercommunication between various information systems because it is not enough to realize the in-depth management of health information. To address these issues, we design the 5G edge computing-assisted architecture for medical community.

Drone Assisted Robust Emergency Service Management for Elderly Chronic Disease.

It is important to monitor the early screening of chronic diseases, predict the risk, and provide the comprehensive management of chronic diseases for the elderly. However, it is difficult to provide the robust and real-time emergency service for elderly chronic disease because of the complex social network and diversity of elderly chronic disease service. To address these issues, we design a new drone assisted robust emergency service system.

Deep Semantic Segmentation of Kidney and Space-Occupying Lesion Area Based on SCNN and ResNet Models Combined with SIFT-Flow Algorithm.

Renal segmentation is one of the most fundamental and challenging task in computer aided diagnosis systems. In order to overcome the shortcomings of automatic kidney segmentation based on deep network for abdominal CT images, a two-stage semantic segmentation of kidney and space-occupying lesion area based on SCNN and ResNet models combined with SIFT-flow transformation is proposed in paper, which is divided into two stages: image retrieval and semantic segmentation. To facilitate the image retrieval, a metric learning-based approach is firstly adopted to construct a deep convolutional neural network structure using SCNN and ResNet network to extract image features and minimize the impact of interference factors on features, so as to obtain the ability to represent the abdominal CT scan image with the same angle under different imaging conditions.