Results 61 to 70 of about 1,984 (174)

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

Implementation of the Random Forest Algorithm with Optuna Optimization in Lung Cancer Classification

SISTEMASI
Lung cancer remains one of the leading causes of death worldwide, with many sufferers unaware of their condition until it is too late for treatment. Therefore, high-accuracy prediction methods are urgently needed for early detection of lung cancer.
Ahmad Ainul Yaqin, Mula Agung Barata, Nur Mahmudah   +2 more
openaire   +2 more sources

Estimation of pulmonary function from time‐resolved dynamic chest radiography using machine learning in patients with respiratory disease

Journal of Applied Clinical Medical Physics, Volume 27, Issue 8, August 2026.
Abstract Background Pulmonary function tests (PFTs), particularly spirometry, are the reference standard for assessing airflow limitation in respiratory diseases such as chronic obstructive pulmonary disease (COPD) and interstitial pulmonary disease.
Takehiro Shiinoki, Yuki Yuasa, Tsunahiko Hirano, Maki Asami‐Noyama, Kazuto Matsunaga, Hidekazu Tanaka   +5 more
wiley   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, Volume 2, Issue 4, August 2026.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Graph neural network-based remaining useful life prediction of milling tools using multi-sensor data

Discover Applied Sciences
Forecasting the Remaining Useful Life (RUL) of cutting tools plays a key role in intelligent predictive maintenance and downtime reduction in today’s manufacturing.
Satish Kumar, Dhruvi Ramaiya, Sameer Sayyad, Arunkumar Bongale, Vivek Warke, Vaibhav Joshi   +5 more
doaj   +1 more source

Dynamic, Unconstrained Optimization of Secreted Enzyme Production in Fed‐Batch Fermentation Using Reinforcement Learning

Biotechnology and Bioengineering, Volume 123, Issue 8, Page 2024-2036, August 2026.
ABSTRACT Reinforcement learning (RL) has been used to control a wide range of dynamic processes, especially ones that are too complex to model well or have stochastic environmental perturbations. Fed‐batch fermentations are subject to changes in starting cell growth rates and process variations that can affect cell growth and secreted target production.
Sai Harish Uthravalli, Sakib Ferdous, J. Michael Hess, Nigel F. Reuel   +3 more
wiley   +1 more source

SSEL‐CPP: A SHAP‐based feature‐selection ensemble learning framework identifies molecular properties of cell‐penetrating peptides

Protein Science, Volume 35, Issue 8, August 2026.
Abstract Cell‐penetrating peptides (CPPs) facilitate the intracellular delivery of therapeutic molecules. However, their accurate identification and design remain challenging because of the complexity of their structural and physicochemical characteristics.
Chan Woo Kwon, Minjun Kwon, Shaherin Basith, Sampa Misra, Yong Eun Jang, Gwang Lee   +5 more
wiley   +1 more source

Optimizing Categorical Boosting Model with Optuna for Anti-Tuberculosis Drugs Classification

Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Tuberculosis is one of the leading causes of death globally, with death rate reaching 1.30 million by 2022, an increase of 3.2% compared to the previous year. Indonesia is one of the countries with the highest number of tuberculosis cases in the world.
null Yosua Satria Bara Harmoni, null Kartika Maulida Hindrayani, null Dwi Arman Prasetya   +2 more
openaire   +1 more source

Beyond Traditional Covariates: An Interpretable Machine Learning Workflow for Improved Hybrid Pharmacometric Modeling

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Model‐informed precision dosing is often constrained by the limited generalizability of traditional population pharmacokinetic models, especially in critically ill patients. A hybrid machine learning‐population pharmacokinetic framework is proposed to improve a priori pharmacokinetic predictions by integrating real‐world clinical data.
Freek J. A. Relouw, Jort J. M. T. Lokers, Tim Preijers, Sebastiaan D. T. Sassen, Natal A. W. van Riel, Birgit C. P. Koch   +5 more
wiley   +1 more source

Application of FCEEMD-TSMFDE and adaptive CatBoost in fault diagnosis of complex variable condition bearings

Scientific Reports
The mode mixing problem and inherent mode function selection bias in Fast Ensemble Empirical Mode Decomposition (FEEMD) result in ineffective extraction of fault components during the denoising stage, the loss of coarse-grained information in Multiscale ...
Min Mao, Bingwei Xu, Yuhuan Sun, Kairong Tan, Yuran Wang, Chao Zhou, Chengjiang Zhou, Jingzong Yang   +7 more
doaj   +1 more source