‘Machine learning’
Effective Learning of 3D Object Detection Models
Understanding the impact of kernel size, dropout ratios, and convolutional layers on a vision model’s performance.
Posted by buchanle on Wednesday, June 25th, 2025 in May 2025, Computer Vision, Machine learning, Model Optimization, Neural Networks, Object Detection
Targeting EZH2 in Cancer: AI-Driven Pipeline for Drug Discov-ery and Optimization
This study introduces an AI-driven approach that predicts and optimizes EZH2 inhibitors by carefully selecting biologically relevant features, significantly improving the efficiency and accuracy of discovering cancer treatments.
Posted by buchanle on Wednesday, June 25th, 2025 in May 2025, Bioinformatics, Drug Discovery, Epigenetics, EZH2, Machine learning
Rhythm of Life: Revolutionizing cardiac diagnostics with AI-driven lub-dub analysis
This study leverages machine learning algorithms to analyze "lub-dub" heart sounds from digital stethoscopes, achieving 98% accuracy in detecting abnormal heartbeat-related heart diseases, offering a breakthrough in non-invasive cardiac diagnostics.
Posted by buchanle on Friday, June 20th, 2025 in May 2025, CVDs, Heart sounds, LSTM, Machine learning, MFCC
A Comparative Analysis of Low-parameter CNN Performance on Malaria Detection from Blood Smear Microscopy
Training lightweight convolutional neural networks to detect malaria from blood smear microscopy to assist medical professionals in diagnosis.
Posted by buchanle on Friday, June 20th, 2025 in May 2025, Artificial Intelligence, convolutional neural networks, Machine learning, Malaria
Cognitive, Genetic, and Lifestyle Synergy: A Machine Learning Approach to Alzheimer’s Diagnosis
This study employs a multidisciplinary approach, integrating machine learning techniques, gene expression analysis, clinical assessments, and lifestyle data to uncover potential biomarkers and therapeutic targets for Alzheimer's disease
Posted by buchanle on Thursday, June 19th, 2025 in May 2025, Alzheimer’s Disease, Cognitive Scores, Diagnosis, Gene Expression, Machine learning
Identifying Reliable Clients for Microlending: A Data-Driven Approach
The research team utilized machine learning in microfinance to predict borrower reliability without relying on traditional credit scores, leveraging data from platforms like Kiva to assess loan risk and promote financial inclusion.
Posted by buchanle on Thursday, June 19th, 2025 in May 2025, Computer Science, Machine learning, Microfinance, Poverty
Water Potability Prediction with Machine Learning
This study aims to build a machine learning tool for rural areas to predict the quality of their water.
Posted by buchanle on Tuesday, April 30th, 2024 in May 2024, Machine learning, Tool, Water Quality
Real-time Machine Learning Detection of Water Pollution using Convolutional Neural Networks
The following paper aims to explore how machine-learning techniques like Convolutional Neural Networks and MultiLayer Perceptron can be used to leverage real-time monitoring data to provide early warning systems for water pollution events, enabling timely response and intervention.
Posted by buchanle on Tuesday, April 30th, 2024 in May 2024, Machine learning, real-time, Water-Pollution
Enhancing Major Depressive Disorder Detection: A Robust Text-Classification Approach using Machine Learning
The objective of the study is to develop a machine learning model that accurately detects Major Depressive Disorder from social media posts
Posted by buchanle on Tuesday, April 30th, 2024 in May 2024, BERT, Depression, Machine learning, Major Depressive Disorder, Text-classification
A Machine Learning Method to Achieve High Accuracy in Galaxy and AGN Classification using Photometric Data
Machine learning enhances active galactic nuclei classification by leveraging photometric data from extensive astronomical surveys.
Posted by buchanle on Tuesday, April 30th, 2024 in May 2024, AGNs, astrophysics, classification, Machine learning, Photometry
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