The authors developed a quantum inspired model for stock market fluctuations.
Read More...Quantum-inspired neural networks enhance stock prediction accuracy
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Towards multimodal longitudinal analysis for predicting cognitive decline
Understanding and predicting cognitive decline in Alzheimer's disease
Read More...Advancing pediatric cancer predictions through generative artificial intelligence and machine learning
Pediatric cancers pose unique challenges due to their rarity and distinct biological factors, emphasizing the need for accurate survival prediction to guide treatment. This study integrated generative AI and machine learning, including synthetic data, to analyze 9,184 pediatric cancer patients, identifying age at diagnosis, cancer types, and anatomical sites as significant survival predictors. The findings highlight the potential of AI-driven approaches to improve survival prediction and inform personalized treatment strategies, with broader implications for innovative healthcare applications.
Read More...Weather-based power outage prediction in New York City: An ensemble machine learning approach
This study contributes to our understanding of how urban energy systems respond to climate variability and inform strategies for enhancing power grid resilience. The findings can help inform urban planners and infrastructure developers by identifying the factors that make regions within a power grid more vulnerable.
Read More...Predicting sickle cell vaso-occlusion by microscopic imaging and modeling
The authors use blood smears from individuals with sickle cell disease to correlate sickle cell frequency with the occurrence of vaso-occlusive crises.
Read More...Applying machine learning to breast cancer diagnosis: A high school student’s exploration using R
The authors combine fine needle aspiration biopsy and machine learning algorithms to develop a breast cancer detection method suitable for resource-constrained regions that lack access to mammograms.
Read More...Simple solving heuristics improve the accuracy of sudoku difficulty classifiers
Cardiovascular Disease Prediction Using Supervised Ensemble Machine Learning and Shapley Values
The authors test the effectiveness of machine learning to predict onset of cardiovascular disease.
Read More...Building deep neural networks to detect candy from photos and estimate nutrient portfolio
The authors use pictures of candy wrappers and neural networks to improve nutritional accuracy of diet-tracking apps.
Read More...Developing a neural network to model the mechanical properties of 13-8 PH stainless steel alloy
We systematically evaluated the effects of raw material composition, heat treatment, and mechanical properties on 13-8PH stainless steel alloy. The results of the neural network models were in agreement with experimental results and aided in the evaluation of the effects of aging temperature on double shear strength. The data suggests that this model can be used to determine the appropriate 13-8PH alloy aging temperature needed to achieve the desired mechanical properties, eliminating the need for many costly trials and errors through re-heat treatments.
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