Results 221 to 230 of about 428,031 (297)

Impact of aging on colon cancer burden: A cross-sectional analysis of nationally representative data. [PDF]

Medicine (Baltimore)
Hou S, Guo T, Chang X, Yang B, Zhou J, Qi L, Li H.   +6 more
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

Development and internal validation of a machine learning model for predicting intracranial infection after spontaneous intracerebral hemorrhage: a two-center retrospective study. [PDF]

Front Neurol
Lin Y, Zheng W, Zhang D, Wang C.
europepmc   +1 more source

Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations

Advanced Electronic Materials, EarlyView.
This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka, Akito Tateyama, Hina Kitano, Takashi Nakanishi, Kazuya Terabe, Takashi Tsuchiya   +5 more
wiley   +1 more source

Association between albumin-based nutritional inflammation indices and all-cause mortality in patients with severe pneumonia. [PDF]

BMC Infect Dis
Qiu X, Sun Q, Liu M, Zhang Y, Jiang Z, Wang Q.   +5 more
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Integration of Time-Varying Pharmacometric Modeling With Cox Regression for Time-to-Event Analysis in NONMEM. [PDF]

CPT Pharmacometrics Syst Pharmacol
Lin CW, Chen PW, Doshi S, Dutta S.
europepmc   +1 more source

Inversion of the Impedance Response Towards Physical Parameter Extraction Using Interpretable Machine Learning

Advanced Energy Materials, EarlyView.
ABSTRACT Interpreting the impedance response of perovskite solar cells (PSCs) is challenging due to the complex coupling of ionic and electronic motion. While drift‐diffusion (DD) modelling is a reliable method, its mathematical complexity makes directly extracting physical parameters from experimental data infeasible.
Mahmoud Nabil, Isel Grau, Ricardo Grau‐Crespo, Said Hamad, Juan A. Anta   +4 more
wiley   +1 more source

Exploring the Predictors of Nurses' Turnover Intentions Through Neural Network Modeling: A National Cross-Sectional Study in Lithuania. [PDF]

Healthcare (Basel)
Žiedelis A, Lazauskaitė-Zabielskė J, Istomina N, Urbanavičė R, Stanislavovienė J.   +4 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source