Results 221 to 230 of about 31,003,301 (345)

Generative AI in clinical practice: how should rheumatologists evaluate and monitor emerging tools?

Arthritis Care &Research, Accepted Article.
Generative artificial intelligence (AI) is increasingly being used in rheumatology practice, to assist with tasks such as documentation, record summarization, and clinical decision support. Rheumatologists need a practical approach to determining what evidence and oversight each application requires.
Koushan Kouranloo, Mrinalini Dey, Jinoos Yazdany   +2 more
wiley   +1 more source

From rules to foundation models: a comprehensive review of machine learning approaches for siRNA design. [PDF]

NAR Genom Bioinform
Khodagholi Z, Yousefi N.
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Integrating Machine Learning Approaches and Topological Indices for Prediction of Electronic Properties in Anticancer Drugs. [PDF]

ACS Omega
Kour S, Sankar JR.
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Visual deep learning approaches for alphabetic sign language interpretation. [PDF]

Sci Rep
Nath JK, Alam SAM, Ullah Y, Dhar M, Dewanjee J, Umair M, Kamal S, Abdullah ZH.   +7 more
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

In Vitro liposome release profile prediction using explainable machine learning approaches. [PDF]

PLoS One
Owida HA, Ahmad Hasan S, Arabiat A, Abuowaida S.   +3 more
europepmc   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Evaluating ensemble learning approaches for horizontal gene transfer detection. [PDF]

Sci Rep
Wijaya AJ, Anžel A, Hattab G.
europepmc   +1 more source