‘Machine learning’
Detection of cyberbullying comments in tweets
XGBoost classifier can be used for cyberbullying detection on social media platforms like Twitter.
Posted by John Lee on Tuesday, May 30th, 2023 in May 2023, Cyberbullying, Machine learning, NLP, Vader Sentiment, XGBoost
Employing Machine Learning Techniques and Frameworks to Aid with Automotive Design
Modifying existing machine learning techniques and architectures to design a new generative model tailored to automotive design.
Posted by John Lee on Tuesday, May 30th, 2023 in May 2023, Automotive Design, Generative Models, Machine learning, Stack-Gan
Automated diagnosis of 7 retinal diseases with convolutional neural networks in a dataset of 2,234 eye images
Automated diagnosis of retinal disease with convolutional neural networks achieving a validation F1-score accuracy of 96% and 95% on cataracts and pathological myopia respectively.
Posted by John Lee on Tuesday, May 30th, 2023 in May 2023, convolutional neural networks, healthcare, Machine learning
Determining the value of a cricket player: Does bowling ability have a greater effect on the rating of a cricket player than batting ability?
Using machine learning to analyze and compare how different variables affect the rating of a cricket player
Posted by John Lee on Tuesday, May 30th, 2023 in May 2023, cricket, Machine learning, regression, Sports analytics
Utilizing Predictive Models to Detect Parkinson’s Disease Via Fractal Scaling
Using Machine Learning to solve Degenerative Diseases
Posted by John Lee on Tuesday, May 30th, 2023 in May 2023, Early Diagnosis, Fractal Scaling, Machine learning, Parkinson’s disease, Voice Detection
Developing cheaper and safer non-weather-based AI models for microgrid demand and supply forecasting in rural areas
This study examines how to make microgrid scheduling using AI forecasting methods simpler, cheaper, and safer using alternative sources of data other than weather data, in order to accelerate the spread of solar power in rural areas.
Posted by John Lee on Tuesday, May 30th, 2023 in May 2023, Artificial Intelligence, Machine learning, microgrid forecasting, renewable energy, rural areas
Providing Recommendations on Combating Climate Change Through Data Driven Analysis
This study applies data science techniques in order to recommend further action toward combating climate change.
Posted by John Lee on Friday, May 19th, 2023 in May 2023, climate change, Machine learning, Sustainability
Removing Dark Region Artifacts using Deep Neural Networks with a Hyperparameter Search
This study used deep neural networks to remove dark region artifacts in order to create clearer ultrasound images.
Posted by John Lee on Wednesday, May 19th, 2021 in May 2021, Deep Neural Network, Machine learning, Ultrasound
Integrating ligand- and receptor-based descriptors in deep neural network QSAR
We demonstrated the functionality of a novel drug discovery technique in a proof-of-concept study.
Posted by John Lee on Tuesday, December 22nd, 2020 in May 2019, Computer-aided drug discovery, deep neural networks, Machine learning, protein binding-pockets, QSAR modeling
Development of a Machine Learning Algorithm for the Prediction of Enhancer Region Activity
A machine learning algorithm was programmed and optimized to predict the activity of enhancer regions of DNA.
Posted by John Lee on Tuesday, December 22nd, 2020 in May 2018, algorithm, enhancer, genetics, Machine learning, prediction