AIMC Topic: China

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Development of a Pancreatic Fistula Prediction Model After Pancreaticoduodenectomy Based on a Decision Tree and Random Forest Algorithm.

The American surgeon
BackgroundThe incidence of postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy (PD) is high. We sought to develop a POPF prediction model based on a decision tree (DT) and random forest (RF) algorithm after PD and to explore its cli...

Subsequence and distant supervision based active learning for relation extraction of Chinese medical texts.

BMC medical informatics and decision making
In recent years, relation extraction on unstructured texts has become an important task in medical research. However, relation extraction requires a large amount of labeled corpus, manually annotating sequences is time consuming and expensive. Theref...

Deep learning method for risk identification of autonomous bus operation considering image data augmentation strategies.

Traffic injury prevention
OBJECTIVE: The autonomous bus is a key application scenario for autonomous driving technology. Identifying the risk of autonomous bus operation is of great significant to improve road traffic safety and promote the large-scale application of autonomo...

Recognizing and monitoring infectious sources of schistosomiasis by developing deep learning models with high-resolution remote sensing images.

Infectious diseases of poverty
BACKGROUND: China is progressing towards the goal of schistosomiasis elimination, but there are still some problems, such as difficult management of infection source and snail control. This study aimed to develop deep learning models with high-resolu...

Mapping Pu'er tea plantations from GF-1 images using Object-Oriented Image Analysis (OOIA) and Support Vector Machine (SVM).

PloS one
Tea is the most popular drink worldwide, and China is the largest producer of tea. Therefore, tea is an important commercial crop in China, playing a significant role in domestic and foreign markets. It is necessary to make accurate and timely maps o...

Early gastric cancer segmentation in gastroscopic images using a co-spatial attention and channel attention based triple-branch ResUnet.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The artificial segmentation of early gastric cancer (EGC) lesions in gastroscopic images remains a challenging task due to reasons including the diversity of mucosal features, irregular edges of EGC lesions and nuances betwe...

Forecasting the energy intensity of industrial sector in China based on FCM-RS-SVM model.

Environmental science and pollution research international
Analysis of industrial energy intensity is greatly significant in China specifically from the perspective of sector heterogeneity due to considerably different levels of energy utilization in various industrial sub-sectors. This study proposes a new ...

Development and validation of questionnaire-based machine learning models for predicting all-cause mortality in a representative population of China.

Frontiers in public health
BACKGROUND: Considering that the previously developed mortality prediction models have limited applications to the Chinese population, a questionnaire-based prediction model is of great importance for its accuracy and convenience in clinical practice...

Automatic medical specialty classification based on patients' description of their symptoms.

BMC medical informatics and decision making
In China, patients usually determine their medical specialty before they register the corresponding specialists in the hospitals. This process usually requires a lot of medical knowledge for the patients. As a result, many patients do not register th...

A hybrid deep learning framework for air quality prediction with spatial autocorrelation during the COVID-19 pandemic.

Scientific reports
China implemented a strict lockdown policy to prevent the spread of COVID-19 in the worst-affected regions, including Wuhan and Shanghai. This study aims to investigate impact of these lockdowns on air quality index (AQI) using a deep learning framew...