Results 181 to 190 of about 48,054 (212)

A CT Lesion Foundation Model for Non‐Invasive Assessment of Hepatocellular Carcinoma Aggressiveness and Prediction of Recurrence Risk

Advanced Science, EarlyView.
A computed tomography lesion foundation model, built by sequential self‐supervised pretraining on generic and hepatocellular carcinoma‐specific lesion images, non‐invasively assesses microvascular invasion and pathological grade from contrast‐enhanced CT and stratifies postoperative recurrence risk.
Wei Xia, Zhehan Shen, Mengsi Li, Jianxin Lu, Ji Xia, Yang Cheng, Wenzheng Li, Shunjie Dong, Lin Deng, Ruokun Li   +9 more
wiley   +1 more source

Reconstruction of large scalp and forehead defects using transposition flaps and guitar-string sutures. a single-center retrospective study. [PDF]

J Dtsch Dermatol Ges
Redondo P.
europepmc   +1 more source

Early‐Life Polyethylene Microplastic Exposure Exacerbates ADHD‐Like Behaviors in Mice via PI3K/AKT1/Nrf2 Signaling: Evidence From the Pilot Cohort and Multi‐Omics Analyses

Advanced Science, EarlyView.
Circulating polyethylene microplastic burden is positively associated with heightened ADHD symptom severity and systemic redox‐inflammatory imbalance in children. Mechanistic investigation in a developmental co‐exposure mouse model further demonstrates that microplastics aggravate ADHD‐like behaviors, dopaminergic dysregulation, and oxidative ...
Yufan Luo, Ruijin Xie, Hua Xu, Xue Xiao, Wei Xiao, Qiyang Pan, Shengjie Xu, Li Liu, Zeliang Xiao, Yue Zhou, Chenyu Sun, Yu Wu, Yueying Liu   +12 more
wiley   +1 more source

Comparative Simulations of Conformational Flexibility during Radical Transport in Ribonucleotide Reductase. [PDF]

Biochemistry
Tremblay M, Hammes-Schiffer S.
europepmc   +1 more source

The Influence of Residual Ion Drift During Programming of Chip‐Integrated Nanoscale HfO2‐Based Memristive Devices

Advanced Electronic Materials, EarlyView.
1T1R‐arrays combining filamentary‐type memristors and CMOS transistors offer great potential for energy‐efficient analog hardware accelerators. Here, transient SET analysis of nanoscale HfO2 memristors integrated on 180 nm CMOS wafers is discussed.
Oliver Artner, Felix Cüppers, Seokki Son, Yang Chen, Xiaohua Liu, Christopher Bengel, Dennis Nielinger, André Zambanini, Stefan Wiefels, Stephan Menzel, Regina Dittmann, Susanne Hoffmann‐Eifert   +11 more
wiley   +1 more source

Transfer learning for honey bee toxicity prediction: MolFormer versus classical QSAR representations. [PDF]

Ecotoxicology
de Souza Pinho AV, de Alencar Filho EB, de Oliveira Neto RF.   +2 more
europepmc   +1 more source

Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation

Advanced Electronic Materials, EarlyView.
A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang, Nellie Laleni, Sina Ranjbar, Andreas Tsiougkos, Nandakishor Yadav, Vasilis Pavlidis, Thomas Kämpfe   +6 more
wiley   +1 more source

Bridging Machine Learning and Algorithmic Information Theory, Part VII: Algorithmic Information Kernels and Kernel Discrepancies on Countable Spaces. [PDF]

Entropy (Basel)
Hamzi B, Hutter M, Owhadi H.
europepmc   +1 more source

Descriptor‐Guided Computational Screening of Non‐Fullerene Acceptor Cores for Organic Solar Cells

Advanced Energy Materials, EarlyView.
We screen over 4000 non‐fullerene acceptors using their ionization energy, electron affinity, quadrupole, and dipole moments to select the top‐ten candidates for a given donor polymer. The workflow recovers known high‐performance motifs and reveals how molecular components influence material properties.
Kun‐Han Lin, J. Terence Blaskovits, Wenlan Liu, Shu‐Yi Hu, Kuei‐Jhong Lin, Sandeep Sharma, Julien Gorenflot, Martin Heeney, Frédéric Laquai, Denis Andrienko   +9 more
wiley   +1 more source

Automatic identification of diagnosis from hospital discharge letters via weakly supervised Natural Language Processing. [PDF]

Sci Rep
Torri V, Barbieri E, Cantarutti A, Giaquinto C, Ieva F.   +4 more
europepmc   +1 more source