Results 71 to 80 of about 4,028 (199)

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

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

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

Interpreting Non‐Linear Compaction Mechanics of Expansive Soils Using Reliability Calibrated Framework

Applied Research, Volume 5, Issue 5, October 2026.
This study introduces a reliability‐calibrated machine learning framework to predict the maximum dry density and optimum moisture content of heterogeneous soils. By integrating 15 algorithms with conformal prediction, the models deliver accurate compaction estimates alongside rigorous, distribution‐free 90% confidence intervals.
Farjad Aziz, Muhammad Waseem, Zeeshan Asghar, Megersa Kebede Leta   +3 more
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

ESpma: A method for assessing biological/non‐biological interfaces using point‐clouds‐based structural features and protein language models

Protein Science, Volume 35, Issue 10, October 2026.
Abstract Distinguishing biological protein–protein interfaces from non‐biological contacts remains an important task in structural biology, particularly as protein complex structures continue to accumulate. Recent advances in protein language models (pLMs) have expanded their use across diverse protein prediction tasks, including sequence‐based protein–
Sarah Nozawa, Kentaro Tomii, Yoshinori Fukasawa   +2 more
wiley   +1 more source

An integrated machine learning and hyperparameter optimization framework for noninvasive creatinine estimation using photoplethysmography signals

Healthcare Analytics
Frequent measurement of creatinine levels is vital for patients with chronic kidney disease. Traditional creatinine level measurement requires invasive blood test which has several disadvantages like discomfort, anxiety, panic, pain, risk of infection ...
Parama Sridevi, Zawad Arefin, Sheikh Iqbal Ahamed   +2 more
doaj   +1 more source

Neural Surrogate HMC: On Using Neural Likelihoods for Hamiltonian Monte Carlo in Simulation‐Based Inference

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Bayesian inference methods such as Markov Chain Monte Carlo (MCMC) typically require repeated computations of the likelihood function, but in some scenarios, this is infeasible and alternative methods are needed. Simulation‐based inference methods address this problem by using machine learning to amortize computations.
L. M. Wolniewicz, P. Sadowski, C. Corti
wiley   +1 more source

Prediksi Laju Inflasi di Jawa Timur Menggunakan Model N-BEATS dan Optimasi Optuna: Prediction of Inflation Rate in East Java Using the N-BEATS Model and Optuna Optimization

Inflasi merupakan indikator penting yang memengaruhi kestabilan dan pertumbuhan ekonomi suatu wilayah. Prediksi inflasi yang akurat sangat dibutuhkan guna mendukung perumusan kebijakan ekonomi yang tepat.
Trimono, Trimono, Riswanda, Mohammad Nizar, Saputra, Wahyu Syaifullah Jauharis   +2 more
core   +1 more source

A Self‐Supervised Framework for Space Object Behaviour Characterisation

Expert Systems, Volume 43, Issue 10, October 2026.
ABSTRACT Foundation Models, which leverage large neural networks pre‐trained on unlabelled data before fine‐tuning for specific tasks, are increasingly being applied to specialised domains. Recent examples include ClimaX for climate and Clay for satellite Earth observation, but a Foundation Model for Space Object Behavioural Analysis (SOBA) has not yet
Ian Groves, Andrew Campbell, James Fernandes, Diego Ramírez Rodríguez, Paul Murray, Massimiliano Vasile, Victoria Nockles   +6 more
wiley   +1 more source