Results 201 to 210 of about 217,331 (267)

Adversarial training collaborating hybrid convolution-transformer network for automatic identification of reactive lymphocytes in peripheral blood. [PDF]

Biomed Opt Express
Mei L, Peng H, Luo P, Jin S, Shen H, He J, Yang W, Ye Z, Sui H, Mei M, Lei C, Xiong B.   +11 more
europepmc   +1 more source

Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images. [PDF]

IEEE Trans Med Imaging, 2020
Mahmood F, Borders D, Chen RJ, Mckay GN, Salimian KJ, Baras A, Durr NJ.   +6 more
europepmc   +1 more source

Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance

Naval Research Logistics (NRL), EarlyView.
ABSTRACT The rapid expansion of cross‐border e‐commerce (CBEC) has created significant opportunities for small‐ and medium‐sized sellers, yet financing remains a critical challenge due to their limited credit histories. Third‐party logistics (3PL)‐led supply chain finance (SCF) has emerged as a promising solution, leveraging in‐transit inventory as ...
Qingkai Zhang, L. Jeff Hong, Houmin Yan
wiley   +1 more source

Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch

Naval Research Logistics (NRL), EarlyView.
ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley   +1 more source

From Data to Decisions: How Machine Learning and Generative Artificial Intelligence Are Redefining Precision Medicine in Kidney Transplantation

Organ Medicine, EarlyView.
This review evaluates how machine learning, multimodal integration, and generative AI optimize kidney transplant outcomes. These tools enable superior prediction and personalized therapy but face hurdles in data volume, generalizability, and ethics. Future clinical adoption depends on continued innovation and multidisciplinary collaboration to overcome
Maoxin Liao, Cheng Yang
wiley   +1 more source

Populism and policy capacity: Evidence from an opposition municipality in Istanbul

Public Administration and Development, EarlyView.
Abstract Despite achievements in its conceptual rigor, policy capacity still represents a relatively depoliticized concept that fails to sufficiently consider the ways in which politics plays a role in its creation, mobilization, or decay. This article seeks to contribute to this debate by investigating the impact of populism on policy capacity, the ...
Ebru Ertugal, Faik Gür, İnan Sevinç
wiley   +1 more source

State Capacity and Path Dependence in Cape Verde's Supreme Audit Institution

Public Administration and Development, EarlyView.
ABSTRACT This study examines state capacity and path dependence in the Supreme Audit Institution (SAI) of Cape Verde, focussing on the performance and governance of the Court of Auditors. Drawing on a mixed‐methods longitudinal design covering the period from 2010 to 2024, the analysis combines international governance indicators, documentary analysis,
Ana Lúcia Romão
wiley   +1 more source

Why do we burn? Examining arguments underpinning the use of prescribed burning to manage wildfire risk

People and Nature, EarlyView.
Abstract Managing wildfire risk requires consideration of complex and uncertain scientific evidence as well as trade‐offs between different values and goals. Conflicting perspectives on what values and goals are most important, what ought to be done and what trade‐offs are acceptable complicate those decisions.
Pele J. Cannon, Sarah Clement
wiley   +1 more source

Six artificial intelligence innovation strategies applied to autism spectrum disorder research: A narrative review

Pediatric Investigation, EarlyView.
Six artificial intelligence strategies advance autism research from tool optimization to paradigm shift: causal modeling, spatiotemporal networks, multimodal integration, digital twins, social cognition mapping, collaborative learning, and context‐aware interventions for precision care.
Ting Zhang, Zhenkun Cao, Wei Li, Zhihai Lv   +3 more
wiley   +1 more source

A composite‐loss graph neural network for the multivariate post‐processing of ensemble weather forecasts

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley   +1 more source