Results 71 to 80 of about 4,087 (203)

Enhanced Retrieval of Raindrop Size Distribution by Integrating Disdrometer Observations and Atmospheric Variables With Machine Learning

Geophysical Research Letters, Volume 53, Issue 19, 16 October 2026.
Abstract Accurate representation of raindrop size distribution (DSD) is crucial for understanding precipitation microphysics and improving quantitative precipitation forecasting. Conventional methods in numerical models often prescribe the DSD shape parameter as a constant or derive it from empirical relationships based solely on disdrometer ...
Limin Lin, Huiling Yuan, Xuwei Bao, Shangshang Yang, Lin Deng, Shuai Zhang, Yuanming Zhao   +6 more
wiley   +1 more source

Anti-Data Leakage Pipeline for Differentiated Thyroid Cancer Recurrence Prediction: Integrating SMOTE, Optuna-based Optimization, and Bootstrap BCa Validation

Journal of Applied Informatics and Computing
Thyroid cancer recurrence prediction remains a critical clinical challenge, as early identification of high-risk patients enables targeted monitoring and intervention.
Deri Rosadi, Sindhu Rakasiwi
doaj   +1 more source

A novel epileptic seizure prediction model based on Cox-Stuart and Optuna

Frontiers in Neurology
Objectives In order to more accurately predict whether patients with intractable epilepsy are about to develop seizures, this paper proposes an epilepsy prediction model. Methods When the amount of targeted patient data is small, A Cox-
Zhang, Xizhen, Zhang, Xiaoli, Chen, Fuming   +2 more
openaire   +2 more sources

Graph Neural Network‐Guided and Interpretable Discovery of Supercapacitor Electrode Materials

Advanced Theory and Simulations, Volume 9, Issue 10, October 2026.
A graph neural network framework combines MEGNet and attention‐enhanced MAGNET to screen over 22 000 DFT‐derived crystal structures for supercapacitor electrodes. It uses formation energy, stability, and band‐gap filtering with Pareto scoring, Monte Carlo Dropout uncertainty, and capacitance classifiers, achieving 90% agreement with cross‐validation ...
Jeffin Kurian Mathews, Aaditya Sharma, Baskaran Kannan, Michael William Fowler, Shankar Raman Dhanushkodi   +4 more
wiley   +1 more source

LightGBM for Liver Disease Detection with Hybrid Hyperparameter Optimization

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
In response to the growing burden of liver-related disorders, this research develops a supervised learning approach using the Light Gradient Boosting Machine (LightGBM) algorithm to support the early identification of Non-Alcoholic Fatty Liver Disease ...
Fajar Ratnawati, Agus Tedyyana, Johny Custer   +2 more
doaj   +1 more source

Optimization of The Machine Learning Approach using Optuna in Heart Disease Prediction

Journal Medical Informatics Technology, 2023
Heart disease prediction is a critical area in healthcare, as early identification and accurate assessment of cardiovascular risks can lead to improved patient outcomes. This study explores the application of machine learning techniques for predicting heart disease.
openaire   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, Volume 2, Issue 5, October 2026.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Multimodal Video Summarization Using Vision‐Language Embeddings and Hierarchical Temporal Modeling

Applied AI Letters, Volume 7, Issue 3, October 2026.
Combining BLIP‐2 image captions with CLIP vision–language embeddings gives video frames semantic meaning that pixels alone cannot convey. Processed by a multi‐scale temporal U‐Net and hierarchical shot‐aware transformer, these multimodal features achieve a state‐of‐the‐art 59.27% F1‐score on SumMe using only 28.27M parameters.
Saadman Sakib, Kaushik Deb
wiley   +1 more source

Optuna Tuning Results PPO Reinforcement Learning Hyperparameters Performance

Systematic hyperparameter tuning using Optuna was expected to improve PPO model performance in a multi-microgrid environment. We hypothesized that optimizing hyperparameters like learning rate and network architecture would enhance model performance ...
Messlem, A (via Mendeley Data)
core   +1 more source

A Multimodal Deep Learning Based Framework for Early and Accurate Diagnosis of Depression Using Electroencephalography and Event‐Related Potential Signals

Applied AI Letters, Volume 7, Issue 3, October 2026.
Cross Wavelet Transform (XWT) is combined with a pre‐trained AlexNet to extract rich time‐frequency features from non‐stationary EEG signals. Also, the proposed framework simultaneously extracts and integrates spatial (Node2vec), time‐frequency (XWT + AlexNet), and spectral (PSD + TSCN) features from EEG and ERP signals within a parallel architecture ...
Atefeh Abedzadeh Attar, Mohammad Hossein Moattar, Yahya Forghani   +2 more
wiley   +1 more source