AI Medical Compendium Topic

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Deep Learning-Based Sentiment Analysis of COVID-19 Vaccination Responses from Twitter Data.

Computational and mathematical methods in medicine
The COVID-19 pandemic has had a devastating effect on many people, creating severe anxiety, fear, and complicated feelings or emotions. After the initiation of vaccinations against coronavirus, people's feelings have become more diverse and complex. ...

Forecasting intermittent and sparse time series: A unified probabilistic framework via deep renewal processes.

PloS one
Intermittency are a common and challenging problem in demand forecasting. We introduce a new, unified framework for building probabilistic forecasting models for intermittent demand time series, which incorporates and allows to generalize existing me...

Research on Lightweight Citrus Flowering Rate Statistical Model Combined with Anchor Frame Clustering Optimization.

Sensors (Basel, Switzerland)
At present, learning-based citrus blossom recognition models based on deep learning are highly complicated and have a large number of parameters. In order to estimate citrus flower quantities in natural orchards, this study proposes a lightweight cit...

Marine Data Prediction: An Evaluation of Machine Learning, Deep Learning, and Statistical Predictive Models.

Computational intelligence and neuroscience
Nowadays, ocean observation technology continues to progress, resulting in a huge increase in marine data volume and dimensionality. This volume of data provides a golden opportunity to train predictive models, as the more the data is, the better the...

Navigating the pitfalls of applying machine learning in genomics.

Nature reviews. Genetics
The scale of genetic, epigenomic, transcriptomic, cheminformatic and proteomic data available today, coupled with easy-to-use machine learning (ML) toolkits, has propelled the application of supervised learning in genomics research. However, the assu...

Machine learning approach for the prediction of postpartum hemorrhage in vaginal birth.

Scientific reports
Postpartum hemorrhage is the leading cause of maternal morbidity. Clinical prediction of postpartum hemorrhage remains challenging, particularly in the case of a vaginal birth. We studied machine learning models to predict postpartum hemorrhage. Wome...

Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review.

Journal of clinical epidemiology
OBJECTIVES: Missing data is a common problem during the development, evaluation, and implementation of prediction models. Although machine learning (ML) methods are often said to be capable of circumventing missing data, it is unclear how these metho...

Detection of Fake News Text Classification on COVID-19 Using Deep Learning Approaches.

Computational and mathematical methods in medicine
A vast amount of data is generated every second for microblogs, content sharing via social media sites, and social networking. Twitter is an essential popular microblog where people voice their opinions about daily issues. Recently, analyzing these o...

Research on GDP Forecast Analysis Combining BP Neural Network and ARIMA Model.

Computational intelligence and neuroscience
Based on the BP neural network and the ARIMA model, this paper predicts the nonlinear residual of GDP and adds the predicted values of the two models to obtain the final predicted value of the model. First, the focus is on the ARMA model in the univa...

Machine learning random forest for predicting oncosomatic variant NGS analysis.

Scientific reports
Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analyzing variants at each run requires considerable time, and we are still struggling with some variants that appear correct on the metrics at first, but ...