AIMC Topic: Databases, Factual

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QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments.

PloS one
BACKGROUND: Over the past decade, machine learning techniques have revolutionized how research and science are done, from designing new materials and predicting their properties to data mining and analysis to assisting drug discovery to advancing cyb...

End-to-End syndrome differentiation of Yin deficiency and Yang deficiency in traditional Chinese medicine.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Yin and Yang, two concepts adapted from classical Chinese philosophy, play a diagnostic role in Traditional Chinese Medicine (TCM). The Yin and Yang in harmonious balance indicate health, whereas imbalances to either side in...

Mammographic Breast Density Assessment Using Deep Learning: Clinical Implementation.

Radiology
Purpose To develop a deep learning (DL) algorithm to assess mammographic breast density. Materials and Methods In this retrospective study, a deep convolutional neural network was trained to assess Breast Imaging Reporting and Data System (BI-RADS) b...

Using neural attention networks to detect adverse medical events from electronic health records.

Journal of biomedical informatics
The detection of Adverse Medical Events (AMEs) plays an important role in disease management in ensuring efficient treatment delivery and quality improvement of health services. Recently, with the rapid development of hospital information systems, a ...

Validation of deep-learning-based triage and acuity score using a large national dataset.

PloS one
AIM: Triage is important in identifying high-risk patients amongst many less urgent patients as emergency department (ED) overcrowding has become a national crisis recently. This study aims to validate that a Deep-learning-based Triage and Acuity Sco...

Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.

Nature biomedical engineering
The detection and removal of precancerous polyps via colonoscopy is the gold standard for the prevention of colon cancer. However, the detection rate of adenomatous polyps can vary significantly among endoscopists. Here, we show that a machine-learni...

Estimating Missing Data in Temporal Data Streams Using Multi-Directional Recurrent Neural Networks.

IEEE transactions on bio-medical engineering
Missing data is a ubiquitous problem. It is especially challenging in medical settings because many streams of measurements are collected at different-and often irregular-times. Accurate estimation of the missing measurements is critical for many rea...

Efficient Brain Tumor Segmentation With Multiscale Two-Pathway-Group Conventional Neural Networks.

IEEE journal of biomedical and health informatics
Manual segmentation of the brain tumors for cancer diagnosis from MRI images is a difficult, tedious, and time-consuming task. The accuracy and the robustness of brain tumor segmentation, therefore, are crucial for the diagnosis, treatment planning, ...

Prediction of spinal curve progression in Adolescent Idiopathic Scoliosis using Random Forest regression.

Computers in biology and medicine
BACKGROUND: The progression of the spinal curve represents one of the major concerns in the assessment of Adolescent Idiopathic Scoliosis (AIS). The prediction of the shape of the spine from the first visit could guide the management of AIS and provi...