AIMC Topic: Humans

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Application research of pulse signal physiology and pathology feature mining in the field of disease diagnosis.

Computer methods in biomechanics and biomedical engineering
This experiment is based on the principle of traditional Chinese medicine (TCM) pulse diagnosis, the human pulse signal collected by the sensor is organized into a dataset, and the algorithms are designed to apply feature extraction. After denoising,...

Diagnostic validation of a deep learning nodule detection algorithm in low-dose chest CT: determination of optimized dose thresholds in a virtual screening scenario.

European radiology
OBJECTIVES: This study was conducted to evaluate the effect of dose reduction on the performance of a deep learning (DL)-based computer-aided diagnosis (CAD) system regarding pulmonary nodule detection in a virtual screening scenario.

Robotic left-stapled total intracorporeal bowel anastomosis versus stapled partial extracorporeal anastomosis: operative technical description and outcomes.

Surgical endoscopy
BACKGROUND: Although there is extensive literature on robotic total intracorporeal anastomosis (TICA) for right colon resection, left total ICA using the da Vinci Xi robotic platform has only been described in short case series previously. In this st...

High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.

European radiology
OBJECTIVES: To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26 kg/m,...

A multi-task two-path deep learning system for predicting the invasiveness of craniopharyngioma.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Craniopharyngioma is a kind of benign brain tumor in histography. However, it might be clinically aggressive and have severe manifestations, such as increased intracranial pressure, hypothalamic-pituitary dysfunction, and vi...

Human-computer interaction based interface design of intelligent health detection using PCANet and multi-sensor information fusion.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: At present, because health monitoring using human-computer interaction (HCI) has become a demand in society, an intelligent health detector with HCI characteristics is urgently needed. Our device and software framework can p...

Accuracy of auto-identification of the posteroanterior cephalometric landmarks using cascade convolution neural network algorithm and cephalometric images of different quality from nationwide multiple centers.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: The purpose of this study was to evaluate the accuracy of auto-identification of the posteroanterior (PA) cephalometric landmarks using the cascade convolution neural network (CNN) algorithm and PA cephalogram images of a different qual...

Informing deep neural networks by multiscale principles of neuromodulatory systems.

Trends in neurosciences
Our brains have evolved the ability to configure and adapt their processing states to match the unique challenges of acting and learning in diverse environments and behavioral contexts. In biological nervous systems, such state specification and adap...

Necessity of Local Modification for Deep Learning Algorithms to Predict Diabetic Retinopathy.

International journal of environmental research and public health
Deep learning (DL) algorithms are used to diagnose diabetic retinopathy (DR). However, most of these algorithms have been trained using global data or data from patients of a single region. Using different model architectures (e.g., Inception-v3, Res...

E-TBNet: Light Deep Neural Network for Automatic Detection of Tuberculosis with X-ray DR Imaging.

Sensors (Basel, Switzerland)
Currently, the tuberculosis (TB) detection model based on chest X-ray images has the problem of excessive reliance on hardware computing resources, high equipment performance requirements, and being harder to deploy in low-cost personal computer and ...