Results 101 to 110 of about 7,680 (217)

Association between occupational lead exposure and multiple health indicators: A machine learning-based study

环境与职业医学
BackgroundLead (Pb) is a highly toxic heavy metal that accumulates in the body, potentially leading to multi-systemic impairment. Compared with traditional statistical methods, machine learning techniques offer unique advantages, opening new avenues for ...
Jiali QIAN, Boshen WANG, Qinheng ZHU, Xiaoru DAI, Baoli ZHU   +4 more
doaj   +1 more source

Advanced Machine Learning Techniques for Corporate Bankruptcy Prediction: A Gradient Boosting TreeNet Approach

Intelligent Systems in Accounting, Finance and Management, Volume 33, Issue 3, September 2026.
ABSTRACT This study aims to enhance bankruptcy prediction models by employing the gradient‐boosting TreeNet algorithm. This research assesses the predictive accuracy of TreeNet in bankruptcy classification using a high‐dimensional approach. Specifically, it categorizes bankruptcy as nonbankrupt, Chapter 7, or Chapter 11 categories.
Ali Saeedi
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

Implementasi Algoritma Catboost Dan Shapley Additive Explanations (SHAP) Dalam Memprediksi Popularitas Game Indie Pada Platform Steam

Jurnal Teknologi Informasi dan Ilmu Komputer
Meningkatnya popularitas game indie di pasar game mewajibkan para pengembang game indie bersaing untuk membuat game nya diminati oleh para pengguna dengan berbagai cara agar dapat meningkatkan potensi popularitasnya.
Mohammad Teddy Syamkalla, Siti Khomsah, Yohani Setya Rafika Nur   +2 more
doaj   +1 more source

Integrative Identification of Anti‐Photoaging Peptides From Stress‐Tolerant Microorganisms via Machine Learning and KEAP1–NRF2 Docking

Journal of Peptide Science, Volume 32, Issue 8, August 2026.
Novel short‐chain peptides targeting the KEAP1‐NRF2 axis were identified through a multimodal discovery platform combining a stress‐tolerant microbial library with machine learning and molecular docking. These peptides regulate collagen synthesis and reduce MMP1/9 levels in human fibroblasts, providing significant protection against photoaging ...
Hanui Lee, Gyeong Han Jeong, Ji Wan Choi, Taehwan Kim, Younhee Shin, Jaewon Lim, Kwang‐Woo Jung, Byung Yeoup Chung, Seung Sik Lee   +8 more
wiley   +1 more source

Student’s Digital Intentions Prediction Using CatBoost

JTP - Jurnal Teknologi Pendidikan
Digital Education and Entrepreneurial (DE) represents a new paradigm in Education and Entrepreneurial that leverages digital technology to create, manage, and expand businesses. By integrating advanced digital tools and platforms, DE plays a crucial role in reshaping traditional business models, driving innovation faster, and enabling enterprises to ...
Zulwisli, Ambiyar, Muhammad Anwar, Andhika Herayono   +3 more
openaire   +3 more sources

Modelling Future Evolution of the Antarctic Ice Sheet With Explainable Machine Learning

Journal of the Royal Society of New Zealand, Volume 56, Issue 4, August 2026.
The accelerating effects of climate change, particularly rising sea levels resulting from melting land ice, require accurate predictions of ice sheet dynamics. Traditional numerical models, such as the Parallel Ice Sheet Model (PISM), are widely used; however, they rely on simplifying assumptions and are computationally intensive, limiting their ...
Paula Maddigan, Bach Hoai Nguyen, Peter Yu Feng Siew, Bing Xue, Nicholas Golledge, Mengjie Zhang   +5 more
wiley   +1 more source

One to Three‐Day Lead Streamflow Forecast Using Multi‐Head Attention With Long Short‐Term Memory in Reservoir Regulated Catchment

Water Resources Research, Volume 62, Issue 8, August 2026.
Abstract Accurate, timely, and actionable flood forecasting has potential for reducing flood risk but remains challenging due to uncertainties in meteorological forecasts, poor hydrological observations, and increasing forecast errors with lead time. While Long Short‐Term Memory (LSTM) models have surpassed conventional hydrological forecasting models,
Hiren Solanki, A. S. Aravinthakshan, Sayuj Gupta, Vimal Mishra   +3 more
wiley   +1 more source

Integrating Artificial Intelligence Into Drug Discovery From Medicinal Plants: Current Applications and Infrastructural Challenges

Chemical Biology &Drug Design, Volume 108, Issue 2, August 2026.
This review presents a systems‐oriented roadmap for integrating artificial intelligence into medicinal plant drug discovery to overcome persistent bottlenecks like extract complexity. It highlights that advancing toward reproducible therapeutics requires making phytochemical datasets AI‐ready via rigorous harmonization and phyto‐centric foundational ...
Amit Gangwal, Azim Ansari, Mohd Usman Mohd Siddique, Jyotiram Sawale, Suhas Padmane, Raju Wadekar   +5 more
wiley   +1 more source

Temporal Drivers of Opioid‐Related ED Visits: An Ensemble Machine Learning Study With Consensus‐Based Feature Attribution

Clinical and Translational Science, Volume 19, Issue 8, August 2026.
ABSTRACT Identification of modifiable risk factors for prescription opioid use disorder (OUD)‐related emergency department (ED) visits (ICD‐10 F11.xx) is a clinical priority; however, most published models remain cross‐sectional and lack pharmacogenomic (PGx) enrichment or dual‐method feature confirmation. Using Virginia All‐Payer Claims Database (APCD)
R. Jerome Dixon, Elvin T. Price
wiley   +1 more source