Results 231 to 240 of about 229,841 (308)

Test-fairness deep learning with influence score. [PDF]

open access: yesPLOS Digit Health
Wu JC   +5 more
europepmc   +1 more source

Deciphering the Crystallinity‐Dependent Sensitivity of Charge Injection in n‐Channel Organic Transistors: Reliable Characterization and Optimized Performance

open access: yesAdvanced Science, EarlyView.
Precise characterization of n‐type organic semiconductors necessitates decoupling interfacial constraints from intrinsic charge transport. This work reveals that disordered polymers are particularly vulnerable to contact‐limited bottlenecks compared to their crystalline counterparts.
Walid Boukhili   +15 more
wiley   +1 more source

Computationally Evidence‐Grounded Sequence‐First Design of Peptide Binders

open access: yesAdvanced Science, EarlyView.
BOND‐PEP enables controllable, sequence‐first peptide binder design by grounding generation in binding evidence retrieved for each target. It uses topology‐conditioned message passing to integrate relevant peptide examples with the target protein sequence, forming a residue‐level representation that guides the generation of diverse, target‐specific ...
Wenze Ding
wiley   +1 more source

Versatile Co‐Engineering of Immunogenic Cell Death‐Primed Dead Tumor Cell Bodies With Tumor‐Activated MnO2 for cGAS‐STING‐Potentiated Personalized Immunotherapy

open access: yesAdvanced Science, EarlyView.
DTBEI@CS@MnO2, fabricated via modular electrostatic co‐engineering and photothermal/photodynamic immunogenic cell death, specifically responds to the acidic and GSH‐rich tumor microenvironment. This triggers the release of DTBEI that provides tumor antigens, DNA, and DAMPs, as well as the generation of Mn2+, thereby synergistically potentiating cGAS ...
Bolun Xu   +6 more
wiley   +1 more source

Bias and Fairness Across the Healthcare AI Lifecycle: A Clinician-Oriented Review. [PDF]

open access: yesBalkan Med J
Kocak B   +5 more
europepmc   +1 more source

Fusing Direct and Indirect Measurements Through Multi‐Fidelity Learning For Accelerated Electrocaloric Materials Discovery

open access: yesAdvanced Science, EarlyView.
A multi‐fidelity framework integrates sparse direct and abundant indirect electrocaloric measurements. Multi‐objective active learning accelerates BaTiO3‐based electrocaloric materials discovery at –70∘C$^{\circ }{\rm C}$. A diffuse transition enables an electrocaloric strength of 0.06×$\times$10−6 Km/V at –70℃ with an operational temperature span of ...
Bo Wang   +8 more
wiley   +1 more source

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