AIMC Topic: Humans

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Deep learning analysis of clinical course of primary nephrotic syndrome: Japan Nephrotic Syndrome Cohort Study (JNSCS).

Clinical and experimental nephrology
BACKGROUND: Prognosis of nephrotic syndrome has been evaluated based on pathological diagnosis, whereas its clinical course is monitored using objective items and the treatment strategy is largely the same. We examined whether the entire natural hist...

Trends in Robot-Assisted Procedures for General Surgery in the Veterans Health Administration.

The Journal of surgical research
INTRODUCTION: Implementation of robot-assisted procedures is growing. Utilization within the country's largest healthcare network, the Veterans Health Administration, is unclear.

Development and multi-institutional validation of an artificial intelligence-based diagnostic system for gastric biopsy.

Cancer science
To overcome the increasing burden on pathologists in diagnosing gastric biopsies, we developed an artificial intelligence-based system for the pathological diagnosis of gastric biopsies (AI-G), which is expected to work well in daily clinical practic...

Patient communication in radiology: Moving up the agenda.

European journal of radiology
Optimised communication between patients and the imaging team is an essential component of providing patient-centred and value-based care. Communication with patients can be challenging in the setting of busy radiology departments where there is a fo...

Distributed contrastive learning for medical image segmentation.

Medical image analysis
Supervised deep learning needs a large amount of labeled data to achieve high performance. However, in medical imaging analysis, each site may only have a limited amount of data and labels, which makes learning ineffective. Federated learning (FL) ca...

Abnormality classification and localization using dual-branch whole-region-based CNN model with histopathological images.

Computers in biology and medicine
The task of classification and localization with detecting abnormalities in medical images is considered very challenging. Computer-aided systems have been widely employed to address this issue, and the proliferation of deep learning network architec...

HHI-AttentionNet: An Enhanced Human-Human Interaction Recognition Method Based on a Lightweight Deep Learning Model with Attention Network from CSI.

Sensors (Basel, Switzerland)
Nowadays WiFi based human activity recognition (WiFi-HAR) has gained much attraction in an indoor environment due to its various benefits, including privacy and security, device free sensing, and cost-effectiveness. Recognition of human-human interac...

Multi-Modal Brain Tumor Detection Using Deep Neural Network and Multiclass SVM.

Medicina (Kaunas, Lithuania)
Clinical diagnosis has become very significant in today's health system. The most serious disease and the leading cause of mortality globally is brain cancer which is a key research topic in the field of medical imaging. The examination and prognosi...

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry.

Cells
Cellular senescence is a hallmark of aging and a promising target for therapeutic approaches. The identification of senescent cells requires multiple biomarkers and complex experimental procedures, resulting in increased variability and reduced sensi...

Towards Precision Oncology: Enhancing Cancer Screening, Diagnosis and Theragnosis Using Artificial Intelligence.

Current oncology (Toronto, Ont.)
Highly complex and multi-dimensional medical data containing clinical, radiologic, pathologic, and sociodemographic information have the potential to advance precision oncology [...].