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Found 11 papers, 0 papers with code
Enhancing Readmission Prediction with Deep Learning: Extracting Biomedical Concepts from Clinical Texts
A novel aspect of this research involves leveraging the Bio-Discharge Summary Bert (BDSS) model along with principal component analysis (PCA) feature extraction to preprocess data for deep learning model input.
A comprehensive cross-language framework for harmful content detection with the aid of sentiment analysis
We collected a Persian dataset and applied the annotation guideline for harmful detection and sentiment analysis.
Dental Severity Assessment through Few-shot Learning and SBERT Fine-tuning
Dental diseases have a significant impact on a considerable portion of the population, leading to various health issues that can detrimentally affect individuals' overall well-being.
Deep Neural Decision Forest: A Novel Approach for Predicting Recovery or Decease of COVID-19 Patients with Clinical and RT-PCR
This study can provide guidance for medical professionals in the event of a crisis or outbreak similar to COVID-19.
Discovering the Symptom Patterns of COVID-19 from Recovered and Deceased Patients Using Apriori Association Rule Mining
Association rule mining is a machine learning technique for extracting hidden patterns from data.
BioBERT Based SNP-traits Associations Extraction from Biomedical Literature
Scientific literature contains a considerable amount of information that provides an excellent opportunity for developing text mining methods to extract biomedical relationships.
Political Sentiment Analysis of Persian Tweets Using CNN-LSTM Model
In this paper, we present several machine learning and a deep learning model to analysis sentiment of Persian political tweets.
A Survey From Distributed Machine Learning to Distributed Deep Learning
Distributed deep learning has gained more attention in recent years and most of the studies have focused on this approach.
Persian Typographical Error Type Detection Using Deep Neural Networks on Algorithmically-Generated Misspellings
Therefore, this paper presents a compelling approach for detecting typographical errors in Persian texts.
Artificial intelligence for Sustainable Energy: A Contextual Topic Modeling and Content Analysis
Parallel to the rising debates over sustainable energy and artificial intelligence solutions, the world is currently discussing the ethics of artificial intelligence and its possible negative effects on society and the environment.
Discourse Analysis of Covid-19 in Persian Twitter Social Networks Using Graph Mining and Natural Language Processing
This analysis is done based on Covid-related posts over eight episodes.
