Results 131 to 140 of about 3,064,133 (295)

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu   +8 more
wiley   +1 more source

Bending‐Resistant Intimate 3D Graphene–Metal Heterojunctions for Highly Sensitive and Robust Flexible Sensors

open access: yesAdvanced Science, EarlyView.
A reservoir‐guided silver‐nanoparticle soldering strategy is developed for bending‐resistant 3D graphene–metal heterojunctions. Controlled hot‐plate evaporation confines conductive ink within the metal reservoir, suppressing spreading and protecting the LIG interface from deformation‐induced fracture.
Saeyoung Park   +5 more
wiley   +1 more source

Single‐Cell RNA Editing Identifies T Cell ADAR1 as a Key Regulator of Immune Exhaustion and Anti‐PD‐1 Resistance in Colorectal Cancer

open access: yesAdvanced Science, EarlyView.
Single‐cell RNA editing analysis identifies ADAR1 as a regulator of dysfunctional T cell states in colorectal cancer. Elevated ADAR1 activity promotes T cell exhaustion and impairs antitumor immunity partly through TGF‐β‐SMAD signaling, contributing to anti‐PD‐1 resistance and highlighting T cell ADAR1 as a potential therapeutic target and biomarker ...
Da Kang   +10 more
wiley   +1 more source

Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors

open access: yesAdvanced Science, EarlyView.
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu   +4 more
wiley   +1 more source

Validation procedures in radiological diagnostic models. Neural network and logistic regression [PDF]

open access: yes
The objective of this paper is to compare the performance of two predictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods.
Pedro Delicado   +2 more
core  

Receiver operating characteristic (ROC) curves of mammography and breast MRI.

open access: yes, 2014
Receiver operating characteristic (ROC) curves of mammography and breast MRI.
Yi Zhao (14034)   +5 more
core   +1 more source

Condition‐Associated Pattern Extraction and Recovery From Multi‐Condition Single‐Cell RNA‐seq Data With CAPER

open access: yesAdvanced Science, EarlyView.
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li   +6 more
wiley   +1 more source

An Integrative Strategy Delineates Modular Metabolic Remodeling and Potential Therapeutic Targets Across Metabolic Diseases

open access: yesAdvanced Science, EarlyView.
An integrative single‐cell atlas across multiple metabolic diseases reveals coordinated metabolic modules and disease‐shared versus disease‐specific pathway activities. By systematically comparing scoring strategies, a robust RankAve framework is established. Coupled with network analysis and drug‐target prediction, this resource uncovers cross‐disease
Kuan Yang   +10 more
wiley   +1 more source

Receiver operating characteristic (ROC) curves for different machine learning models.

open access: yes, 2018
Receiver operating characteristic (ROC) curves for different machine learning models.
Kei-Hoi Cheung (4729)   +3 more
core   +1 more source

Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature

open access: yesAdvanced Science, EarlyView.
A deep learning model analyzes cfRNA profiles extracted from the blood of OVCA patients. This innovative approach distinguishes OVCA from healthy controls with high accuracy. Crucially, it reliably predicts patient response to chemotherapy (sensitive versus resistant subgroups).
Qinhao Guo   +14 more
wiley   +1 more source

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