Results 71 to 80 of about 3,964 (194)

Optimizing XGBoost for Heart Disease Risk Classification Using Optuna and Random Search on the Behavioral Risk Factor Surveillance System (BRFSS) 2023 Dataset

Journal of Applied Informatics and Computing
Heart disease is a critical public health issue in Indonesia, contributing to approximately 1,5 million deaths annually. Although machine learning methods, particularly Extreme Gradient Boosting (XGBoost), have demonstrated strong performance in medical ...
Muhammad Dzaky, Adam Prayogo Kuncoro, Riyanto Riyanto   +2 more
doaj   +1 more source

A Semi‐Automated Microfluidic Platform Employing Machine Learning Analysis to Study Adhesion Kinetics in Acute Myeloid Leukemia

Microscopy Research and Technique, EarlyView.
We have developed a semi‐automated shear flow platform using bright‐field optics and a machine‐learning analysis algorithm to dissect tumor‐microenvironment interactions. The algorithm quantifies the extent of adhesion at the single‐cell level and delivers consistent results within minutes instead of hours, facilitating high‐throughput analysis ...
Driti Ashok, Dennis Raith, Gabriel Kalweit, Maria Kalweit, Anusha Klett, Justus Duyster, Jonas Bermeitinger, Tanja Nicole Hartmann   +7 more
wiley   +1 more source

Forecasting Topic, Word, and Hashtag Popularity on X (Twitter) Using LightGBM for Digital Marketing Optimization

Journal of Applied Informatics and Computing
This study presents a machine learning, based framework to forecast the popularity of topics, words, and hashtags on platform X (Twitter) for data-driven digital marketing optimization.
Deannisa Syafira Putri, Amri Muhaimin, Mohammad Idhom   +2 more
doaj   +1 more source

Unraveling the Spatiotemporal Dynamics and Nonlinear Drivers of Green Transition of Farmland Use in Major Grain‐Producing Areas: A Case Study of Jiangsu Province, China

Land Degradation &Development, EarlyView.
ABSTRACT Promoting the green transition of farmland use (GTFU) in major grain‐producing areas is essential for ensuring food security and advancing sustainable agricultural development. However, existing studies on GTFU have predominantly relied on static cross‐sectional analyses, with insufficient attention paid to its nonlinear driving mechanisms. To
Zhixian Sun, Yixuan Lu, Xinyue Zheng, Dongmei Zhang, Yian Xu, Guanxin Yao   +5 more
wiley   +1 more source

A Deep Learning Approach to Alzheimer's Diagnosis Using EEG Data: Dual-Attention and Optuna-Optimized SVM. [PDF]

Biomedicines
Background/Objectives: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder, pathologically defined by the accumulation of amyloid-β plaques and tau-related neurofibrillary tangles in the brain.
Arikan FB, Cetintas D, Aksoy A, Yildirim M.   +3 more
europepmc   +2 more sources

A Context‐Aware Decision Support Framework for Scientific Experiment Configuration

Software: Practice and Experience, EarlyView.
ABSTRACT Introduction Defining an experimental configuration is a complex decision problem for early‐stage researchers, who must map goals, constraints, and requirements onto datasets, algorithms, and parameter settings that directly affect experimental outcomes.
Pouriya Miri, Vlado Stankovski, Kristina Veljković, Petar Kochovski   +3 more
wiley   +1 more source

Decreasing the Environmental Impact of the Electric Steelmaking Route Through Advanced Modelling Techniques

steel research international, EarlyView.
Ensemble models are adopted to estimate the sterile content of scraps arriving to the scrap yard. Feed‐forward neural networks are exploited to estimate steel composition and temperature after Ladle furnace. The models are validated on data from two steelworks very satisfactory results and are inherently transferable to other steelworks, as they are ...
Valentina Colla, Antonella Zaccara, Stefano Dettori, Laura Laid, Ismael Matino, Silvia Cateni, Teresa Annunziata Branca, Lorenzo Vannini   +7 more
wiley   +1 more source

Interactive segmentation of membrane and membrane‐mimic densities in cryo‐EM maps

Acta Crystallographica Section D, EarlyView.
SURFER performs automated segmentation of contextual membrane and membrane‐mimic density in cryo‐EM maps to enable robust separation of macromolecular signal from surrounding detergent or lipid–membrane features. It is conveniently distributed as a plugin for UCSF ChimeraX, allowing interactive application within standard map‐visualization workflows ...
Alok Bharadwaj, Lotte Veerbeek, Arjen Jakobi   +2 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

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