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Found 8 papers, 3 papers with code
Machine Learning Predicts Upper Secondary Education Dropout as Early as the End of Primary School
The machine learning models developed in this study demonstrated notable classification ability, achieving a mean area under the curve (AUC) of 0. 61 with data up to Grade 6 and an improved AUC of 0. 65 with data up to Grade 9.
Deep Fast Vision: A Python Library for Accelerated Deep Transfer Learning Vision Prototyping
Deep learning-based vision is characterized by intricate frameworks that often necessitate a profound understanding, presenting a barrier to newcomers and limiting broad adoption.
Exploring the Efficacy of Base Data Augmentation Methods in Deep Learning-Based Radiograph Classification of Knee Joint Osteoarthritis
Our study underscores the need for careful technique selection for improved model performance and identifying and managing potential confounding regions in radiographic KOA deep learning.
Adaptive Variance Thresholding: A Novel Approach to Improve Existing Deep Transfer Vision Models and Advance Automatic Knee-Joint Osteoarthritis Classification
This approach led to two key outcomes: an increase in the initial accuracy of the pre-trained KOA models and a 60-fold reduction in the NAS input vector space, thus facilitating faster inference speed and a more efficient hyperparameter search.
Synthesizing Bidirectional Temporal States of Knee Osteoarthritis Radiographs with Cycle-Consistent Generative Adversarial Neural Networks
Knee Osteoarthritis (KOA), a leading cause of disability worldwide, is challenging to detect early due to subtle radiographic indicators.
Improving Performance in Colorectal Cancer Histology Decomposition using Deep and Ensemble Machine Learning
However, recent research highlights the potential of convolutional neural networks (CNNs) in facilitating the extraction of clinically relevant biomarkers from these readily available images.
Keras GPT Copilot: Integrating the Power of Large Language Models in Deep Learning Model Development
Keras GPT Copilot is the first Python package designed to integrate an LLM copilot within the model development workflow, offering iterative feedback options for enhancing the performance of your Keras deep learning models.
Deep Fast Vision: Accelerated Deep Transfer Learning Vision Prototyping and Beyond
Deep Fast Vision is a versatile Python library for rapid prototyping of deep transfer learning vision models.
