Results 51 to 60 of about 197,316 (278)

Stroke Prediction with Enhanced Gradient Boosting Classifier and Strategic Hyperparameter [PDF]

A stroke is a medical condition that occurs when the blood supply to the brain is interrupted. Stroke can cause damage to the brain that can potentially affect a person’s function and ability to move, speak, think, and feel normally. The effect of stroke
Aditya, Christian Sri Kusuma, Chandranegara, Didih Rizki, Gayatri, Agnes Ayu Maharani Dyah, Setyarini, Dela Ananda   +3 more
core   +2 more sources

Natural Products as Geroprotective Modulators in Diabetic Nephropathy: A Mechanistic Framework Integrating Aging Hallmarks and the AMPK–SIRT1–Nrf2 Axis

Aging and Cancer, EarlyView.
Natural products target the aging kidney in diabetic nephropathy by restoring the AMPK–SIRT1–Nrf2 axis, reducing oxidative stress, inflammation, fibrosis, and cellular senescence while enhancing mitochondrial biogenesis and antioxidant defenses.
Sherif Hamidu, Latif Adams, Eunice Ampem‐Danso, Justice Kumi, Abigail Aning, Fatima Hamidu, Mustapha Abdul Mumin Mohammed, Ayuba Nii Darku Ankrah, Seth Kwabena Amponsah   +8 more
wiley   +1 more source

Applicability of machine learning approaches for predicting the phase formation in complex concentrated alloys

Next Materials
This work deals with the machine learning techniques used to build predictive models to determine the phases in complex concentrated alloys (CCAs). Two different approaches were employed to determine the presence of phases.
Kaven A.S., Subhasis Sinha, Surya D. Yadav   +2 more
doaj   +1 more source

Revisiting Gradient Boosting-Based Approaches for Learning Imbalanced Data: A Case of Anomaly Detection on Power Grids

Big Data and Cognitive Computing, 2022
Gradient boosting ensembles have been used in the cyber-security area for many years; nonetheless, their efficacy and accuracy for intrusion detection systems (IDSs) remain questionable, particularly when dealing with problems involving imbalanced data ...
Maya Hilda Lestari Louk, Bayu Adhi Tama
doaj   +1 more source

Generalized Boosting Algorithms for Convex Optimization [PDF]

, 2011
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks, we analyze gradient-based descent algorithms for boosting with respect to ...
Bagnell, J. Andrew, Grubb, Alexander
core   +1 more source

Prognostic Impact of European LeukemiaNet Genetic Risk Stratification System in Adult Patients With Acute Myeloid Leukemia

Aging and Cancer, EarlyView.
This study aimed to evaluate the prognostic value of ELN2017 in predicting survival outcomes and to assess the impact of clinical and molecular factors such as age, FLT3 and NPM1 mutations, and allogeneic hematopoietic stem cell transplantation (allo‐HSCT).
Mobina Shrestha, Bishwas Mandal, Vishal Mandal, Asis Shrestha, Amir Babu Shrestha   +4 more
wiley   +1 more source

Machine learning regression models for internal shame

Acta Psychologica
This study aims to predict Internal Shame (IS) based on childhood trauma, social emotional competence, cognitive flexibility, distress tolerance and alexithymia in an Iranian sample.
Nataša Kovač, Kruna Ratković, Hojjatollah Farahani, Peter Watson   +3 more
doaj   +1 more source

Totally Corrective Multiclass Boosting with Binary Weak Learners [PDF]

, 2010
In this work, we propose a new optimization framework for multiclass boosting learning. In the literature, AdaBoost.MO and AdaBoost.ECC are the two successful multiclass boosting algorithms, which can use binary weak learners.
Barnes, Nick, Hao, Zhihui, Shen, Chunhua, Wang, Bo   +3 more
core  

Evaluation of a novel EHR sidecar application to display RA clinical outcomes during clinic visits: results of a stepped‐wedge cluster randomized pragmatic trial

Arthritis Care &Research, Accepted Article.
Objective We developed a novel EHR sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk, Jing Li, Cathy Nasrallah, Cherish Wilson, Alicia Hamblin, Christine Hariz, Cammie Young, Stephen Shiboski, Emma Kersey, Mary Nakamura, Judith F. Ashouri, Mehrdad Matloubian, Andrew J. Gross, Jennifer Barton, Beth Berrean, Jonathan Prugh, Jinoos Yazdany   +16 more
wiley   +1 more source

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source