Results 211 to 220 of about 95,729 (269)

Integrating Gene Expression With Recurrent Mutations Improves Age-Stratified Risk Prediction in Acute Myeloid Leukemia. [PDF]

EJHaem
Shrestha M, Dahal S, Shrestha A, McNally P, Shrestha AB, Mackler N.   +5 more
europepmc   +1 more source

Proteomics of Nitrotyrosine: Integrating Mass Spectrometry and Immunodetection in Redox‐Driven Pathology

Mass Spectrometry Reviews, EarlyView.
ABSTRACT Nitrooxidative stress, driven by excess reactive nitrogen species like peroxynitrite, contributes to the pathogenesis of many chronic diseases. Among its molecular footprints, 3‐nitrotyrosine (3NT) has emerged as a biologically relevant marker of protein nitration.
Brîndușa Alina Petre
wiley   +1 more source

Responsible AI for Sepsis Prediction: Bridging the Gap Between Machine Learning Performance and Clinical Trust. [PDF]

J Clin Med
Oliveira TQ, Carvalho LA, Sousa FRC, Filho JBF, Oliveira KF, Tavares DAB.   +5 more
europepmc   +1 more source

The Brain‐Age Gap in Pediatric Dystonia: Neuroanatomical Deviations Inform Deep Brain Stimulation Outcomes

Movement Disorders, EarlyView.
Abstract Background Dystonia in children is a heterogeneous condition with variable response to deep brain stimulation (DBS). Brain‐age gap, a machine learning‐derived metric of structural deviation from norm, may capture signatures that differentiate underlying biotypes and predict outcomes.
Timur H. Latypov, Alexandre Berger, Manuela Mohareb, Karim Mithani, Sara Breitbart, Lindsey M. Vogt, Thiemo Dinger, Inge Meijer, Alexander G. Weil, Alfonso Fasano, Carolina Gorodetsky, George M. Ibrahim   +11 more
wiley   +1 more source

Diagnosis of SLAP lesions on shoulder MRI using a 2.5D deep learning and ensemble learning framework. [PDF]

Front Surg
Wang H, Xue Q, Shi L, Wang F, Gao G, Wang L.   +5 more
europepmc   +1 more source

Experimental Modal Analysis‐Driven Gaussian Process Regression Modeling of Rectangular Steel Beams With Various Hole Geometries

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Understanding the dynamic behavior of structural components is crucial for optimizing performance and ensuring structural integrity. This study presents a new method that combines a systematic experimental investigation of four distinct hole geometries (circular, square, compact rectangular, and long rectangular) with varying hole counts, all ...
Amir Hossein Rabiee, Majid Rajaei, Mohammad Hossein Mahdavi Nasab, Parsa Shafiei   +3 more
wiley   +1 more source

Lessons Learned From Using Simple Supervised Learning Tools on Small‐Ensemble Data—Applicability to Tunnel Design and Monitoring

International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT Integrating interdisciplinary strategies with artificial intelligence (AI), particularly machine learning (ML), is an effective way of addressing urgent engineering challenges. Therefore, a thorough evaluation of existing methodologies is essential, taking into account their respective strengths, limitations and opportunities.
Lina‐María Guayacán‐Carrillo, Jean‐Michel Pereira, Jean Sulem   +2 more
wiley   +1 more source

A Machine Learning Model for Predicting Recurrent Pregnancy Loss: Retrospective Integration of Routine Serum IL-33, C-Reactive Protein, and Lymphocyte Subset Counts. [PDF]

Int J Gen Med
Liu Q, Dong L.
europepmc   +1 more source

Opening the Black Box of Nonprofit Reputation and Volunteer Attraction With Supervised Machine Learning

Nonprofit Management and Leadership, EarlyView.
ABSTRACT With the aim to explore the potential of machine learning for nonprofit research, this article contrasts traditional linear regression with four contemporary supervised machine learning approaches. Concretely, we predict (1) reputation ratings and (2) the total number of volunteers for 4021 non‐profit organizations in the U.S.
Moritz Schmid, Hannes Lampe, Jurgen Willems   +2 more
wiley   +1 more source