Results 11 to 20 of about 67,243 (217)

Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data

Molecular Oncology, EarlyView.
This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu, Katherine Eason, Suet‐Feung Chin, Paul A. W. Edwards, Raquel Manzano Garcia, Richard Moulange, Jia Wern Pan, Soo Hwang Teo, Sach Mukherjee, Maurizio Callari, Carlos Caldas, Stephen‐John Sammut, Oscar M. Rueda   +12 more
wiley   +1 more source

Understanding and measuring mechanical signals in the tumor stroma

FEBS Open Bio, EarlyView.
This review discusses cancer‐associated fibroblast subtypes and their functions, particularly in relation to extracellular matrix production, as well as the development of 3D models to study tumor stroma mechanics in vitro. Several quantitative techniques to measure tissue mechanical properties are also described, to emphasize the diagnostic and ...
Fàtima de la Jara Ortiz, Chiara Cimmino, Maurizio Ventre, Alessandra Cambi   +3 more
wiley   +1 more source

Beyond digital twins: the role of foundation models in enhancing the interpretability of multiomics modalities in precision medicine

FEBS Open Bio, EarlyView.
This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi, Xin Gao, Takashi Gojobori   +2 more
wiley   +1 more source

An approach for coherent periodogram averaging of tilt‐series data for improved contrast transfer function estimation

FEBS Open Bio, EarlyView.
The contrast transfer function (CTF) is an imaging aberration that is a major resolution‐limiting factor in cryo‐electron microscopy (cryo‐EM). Precise CTF estimation is key to overcoming this limitation, but is particularly challenging in cryo‐electron tomography (cryo‐ET) data. Here, we present an approach for using geometric information to assist in
Sagar Khavnekar, William Wan
wiley   +1 more source

Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra‐hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter‐fraction variability, inconsistent patient adherence still results in OAR variability.
Conor Sinclair Smith, Isabelle Gagne, Karl Otto, Carter Kolbeck, Joshua Giambattista, Abraham Alexander, Sonja Murchison, Andrew Pritchard, Erika Chin   +8 more
wiley   +1 more source

Evaluating feature extraction reproducibility across image biomarker standardization initiative‐compliant radiomics platforms using a digital phantom

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background The aim of this study was to thoroughly analyze the reproducibility of radiomics feature extraction across three Image Biomarker Standardization Initiative (IBSI)‐compliant platforms using a digital phantom for benchmarking. It uncovers high consistency among common features while also pointing out the necessity for standardization ...
Han‐Back Shin, Heesoon Sheen, Jang‐Hoon Oh, Young Eun Choi, Kihoon Sung, Hyun Ju Kim   +5 more
wiley   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

International Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez, Mauro Gaggero, Andrea Serani   +2 more
wiley   +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

Elasticity of Diametrically Compressed Microfabricated Woodpile Lattices

Advanced Engineering Materials, EarlyView.
Modulus–porosity relationship is derived for woodpile lattices with struts under diametrical compression. The formula presented here that Young's modulus is proportional to the square of the volume fraction E˜ρ2$E \sim \left(\rho\right)^{2}$ is shown to be consistent with computations and laboratory experiments on 3D‐printed samples.
Faezeh Shalchy, Atul Bhaskar
wiley   +1 more source

Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

Advanced Materials Interfaces, EarlyView., 2023
This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi, Munevver Akdeniz, Awel Olsido Ahmed, Mine Altunbek, Omer Aydin   +4 more
wiley   +1 more source