Results 81 to 90 of about 3,330 (201)

Classification of Alzheimer's Disease Using a Hybrid Technique Integration Between CNN and Optuna Optimization

NTU Journal of Engineering and Technology
Alzheimer's Disease (AD) is considered one of the most prevalent neurological disorders, primarily affecting elderly people and adversely impacting their brain functions. This disease is characterized by the gradual deterioration of cognitive functions,
Nawzt Sadiq Jaafar Al-Bayati, Raid Rafi Omar Al-Nima   +1 more
doaj   +1 more source

A SHAP‐Informed Formal Feature Attribution Framework for Drug–Drug Interaction Risk in Large‐Scale Claims Data

Clinical and Translational Science, Volume 19, Issue 9, September 2026.
ABSTRACT Pairwise drug–drug interaction databases flag co‐prescribed pairs, but they under‐weight multi‐drug combinations that drive adverse drug events in older adults. We studied that gap in Virginia All‐Payer Claims Database records (2016–2019) for adults aged 65–114 years with non‐opioid emergency department visits (n = 1182 cases; 16,105 matched ...
R. Jerome Dixon, Elvin T. Price
wiley   +1 more source

MSPCIFormer: A Multi‐Scale Patching Channel‐Independent Transformer for Cryptocurrency Price Forecasting

Expert Systems, Volume 43, Issue 9, September 2026.
ABSTRACT Forecasting cryptocurrency prices remains challenging due to extreme volatility, regime‐dependent dynamics, and unstable cross‐asset correlations. Statistical methods such as ARIMA and GARCH assume stationarity and linear dependence structures, making them inadequate for capturing non‐linear temporal patterns in high volatile cryptocurrency ...
Huali Zhao, Martin Crane, Marija Bezbradica   +2 more
wiley   +1 more source

Fine-Tuning CNN-BiGRU for Intrusion Detection with SMOTE Optimization Using Optuna [PDF]

Network security faces a significant challenge in developing effective models for intrusion detection within network systems. Network Intrusion Detection Systems (NIDS) are vital for protecting network traffic and preempting potential attacks by ...
BENCHAMA, Asmaa, ZEBBARA, Khalid
core   +2 more sources

The Use of Hyperparameter Tuning in Model Classification: A Scientific Work Area Identification

JOIV: International Journal on Informatics Visualization
This research aims to investigate the effectiveness of hyperparameter tuning, particularly using Optuna, in enhancing the classification performance of machine learning models on scientific work reviews. The study focuses on automating the classification
Nadya Alinda Rahmi, Sarjon Defit, - Okfalisa   +2 more
doaj   +1 more source

Uncertainty‐Aware Machine Learning for Onset of Deep Convection: Under what Conditions Are Trigger Predictions More Reliable?

Geophysical Research Letters, Volume 53, Issue 15, 16 August 2026.
Abstract Machine Learning (ML) models have emerged as a powerful tool for predicting deep convection triggering, yet the atmospheric conditions that systematically challenge these models in detecting deep convection remain poorly understood. To diagnose such ambiguous regimes, we trained a Controlled Abstention Neural Network (CAN) that separates high‐
Ashish Bhattarai, Youtong Zheng
wiley   +1 more source

Case study of Hyperparameter Optimization framework Optuna on a Multi-column Convolutional Neural Network [PDF]

, 2022
To observe the condition of the flower growth during the blooming period and estimate the harvest forecast of the Canola crops, the ‘Flower Counter’ application has been developed by the researchers ofP2IRC at the ...
Jeba, Jenia Afrin
core  

Optimization of diabetes prediction methods based on combinatorial balancing algorithm

Nutrition & Diabetes
Background Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction.
HuiZhi Shao, Xiang Liu, DaShuai Zong, QingJun Song   +3 more
doaj   +1 more source

Development of the Optuna-NGBoost-SHAP model for estimating ground settlement during tunnel excavation

Underground Space
This study aims to develop and evaluate a natural gradient boosting (NGBoost) model optimized with Optuna for estimating ground settlement during tunnel excavation, incorporating Shapley additive explanations (SHAP) to perform interpretability analysis ...
Yuxin Chen, Mohammad Hossein Kadkhodaei, Jian Zhou   +2 more
doaj   +1 more source

Optimized Breast Cancer Classification Using PCA-LASSO Feature Selection and Ensemble Learning Strategies With Optuna Optimization

IEEE Access
Breast cancer is one of the most prevalent and life-threatening diseases among women worldwide, making early and accurate detection crucial for effective treatment.
Prabhat Kumar Sahu, Taiyaba Fatma
doaj   +1 more source