Results 221 to 230 of about 102,874 (306)

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Multi-scale pyramid pooling with low complexity for acoustic scene classification. [PDF]

Sci Rep
Jiang P, Liu X, Li P.
europepmc   +1 more source

Nonlinear Dynamics and Invariants of Motion in ReRAM Cells

Advanced Electronic Materials, EarlyView.
A second‐order cell, hosting one capacitor and two back‐to‐back ReRAMs, admits Invariants of Motion: its states lie on one‐dimensional manifolds at all times. The cell shows quiescent monostability or bistability, depending on the manifold index. At equilibrium, the capacitor voltage vanishes.
Mauro Di Marco, Mauro Forti, Luca Pancioni, Giacomo Innocenti, Alberto Tesi, Alon Ascoli   +5 more
wiley   +1 more source

Application of deep learning in prognostic prediction of non-small cell lung cancer. [PDF]

Front Cell Dev Biol
Lun X.
europepmc   +1 more source

AI‐Assisted Ultrasensitive Biosensing using Metal‐Electrolyte‐Metal‐Insulator‐Silicon Structure Based on Oxygen‐Tunable Iridium Oxide Nanonets for Lysyl‐Oxidase‐Like‐2 Breast Cancer Detection

Advanced Electronic Materials, EarlyView.
An oxygen‐controlled iridium‐oxide (IrOx) nano‐net structure is developed to enhance the sensitivity of metal‐electrolyte‐metal‐insulator‐silicon (MEMIS) biosensors. Integrated with a deep learning model, this platform achieves a high accuracy of 94.8% for detecting the breast cancer biomarker LOXL2.
Chiao‐Fan Chiu, Pankaj Kumar, Long Nguyen Minh Le, Ping‐Hsuan Wu, Punnatorn Boonyoung, Shen Tingyang, Abhijit Aich, Yi‐Pin Chen, Shih‐Yin Huang, Siddheswar Maikap   +9 more
wiley   +1 more source

A comparative analysis of deep learning models for disease classification in multi-organ histopathological images. [PDF]

Sci Rep
Choi JR, Jang S, Oh SS, Lee JY, Kim K, Oh T.   +5 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

Mapping the Influence of Artificial Intelligence in Prosthodontics: A Scoping Review of the Current Trends and Challenges. [PDF]

Dent J (Basel)
Boca DA, Ille CE, Jivanescu A.
europepmc   +1 more source

Artificial Intelligence–Based Surgical Phase Analysis Enables Objective Assessment of Surgeon Skill in Robotic Distal Gastrectomy: A Multicenter Study

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim Artificial intelligence (AI)–based surgical video analysis can automate time‐consuming manual assessments and enable objective characterization of surgical workflows. We aimed to construct a large, multicenter, fully annotated dataset of robotic distal gastrectomy (RDG) videos and evaluate the feasibility and performance of an AI model for
Masaru Komatsu, Daichi Kitaguchi, Yoichi Ninomiya, Yuya Takabe, Mitsumasa Yoshida, Masahiro Yura, Nobuyoshi Takeshita, Takahiro Kinoshita, Masaaki Ito   +8 more
wiley   +1 more source