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A Machine Learning Model for Evaluating Imported Disease Screening Strategies in Immigrant Populations.

The American journal of tropical medicine and hygiene
Given the high prevalence of imported diseases in immigrant populations, it has postulated the need to establish screening programs that allow their early diagnosis and treatment. We present a mathematical model based on machine learning methodologie...

Unifying information theory and machine learning in a model of electrode discrimination in cochlear implants.

PloS one
Despite the development and success of cochlear implants over several decades, wide inter-subject variability in speech perception is reported. This suggests that cochlear implant user-dependent factors limit speech perception at the individual level...

Machine learning risk prediction model for acute coronary syndrome and death from use of non-steroidal anti-inflammatory drugs in administrative data.

Scientific reports
Our aim was to investigate the usefulness of machine learning approaches on linked administrative health data at the population level in predicting older patients' one-year risk of acute coronary syndrome and death following the use of non-steroidal ...

Neural-Network Based Modeling of I/O Buffer Predriver under Power/Ground Supply Voltage Variations.

Sensors (Basel, Switzerland)
This paper presents a neural-network based nonlinear behavioral modelling of I/O buffer that accounts for timing distortion introduced by nonlinear switching behavior of the predriver electrical circuit under power and ground supply voltage (PGSV) va...

Relation classification via BERT with piecewise convolution and focal loss.

PloS one
Recent relation extraction models' architecture are evolved from the shallow neural networks to natural language model, such as convolutional neural networks or recurrent neural networks to Bert. However, these methods did not consider the semantic i...

BERTtoCNN: Similarity-preserving enhanced knowledge distillation for stance detection.

PloS one
In recent years, text sentiment analysis has attracted wide attention, and promoted the rise and development of stance detection research. The purpose of stance detection is to determine the author's stance (favor or against) towards a specific targe...

Automated machine learning for endemic active tuberculosis prediction from multiplex serological data.

Scientific reports
Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Clinical interpretation of these complex datasets requires development of suitable algorithms, a time c...

Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.

PloS one
The study is aimed at the frosting problem of the air source heat pump in the low temperature and high humidity environment, which reduces the service life of the system. First, the frosting characteristics at the evaporator side of the air source he...

Predicting mortality among patients with liver cirrhosis in electronic health records with machine learning.

PloS one
OBJECTIVE: Liver cirrhosis is a leading cause of death and effects millions of people in the United States. Early mortality prediction among patients with cirrhosis might give healthcare providers more opportunity to effectively treat the condition. ...

Toward a Unified Theory of Customer Continuance Model for Financial Technology Chatbots.

Sensors (Basel, Switzerland)
With the popularity of financial technology (fintech) chatbots equipped with artificial intelligence, understanding the user's response mechanism can help bankers formulate precise marketing strategies, which is a crucial issue in the social science ...