Results 211 to 220 of about 97,243 (265)

Data-Efficient Deep Learning Framework for Urolithiasis Detection Using Transfer and Self-Supervised Learning. [PDF]

Int Neurourol J
Kim JS, Eun SJ.
europepmc   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Unbiased self supervised learning of kidney histology reveals phenotypic and prognostic insights. [PDF]

Sci Rep
Pandit K, Coudray N, Quiros AC, Surapaneni A, Upadhyay D, Vanguri RS, Hirohama D, Mohandes S, Schlosser P, Thiessen-Philbrook H, Wen Y, Parikh CR, Rhee EP, Waikar SS, Schmidt I, Rosenberg AZ, Palmer MB, Susztak K, Grams ME, Tsirigos A, TRIDENT Study Investigators.   +20 more
europepmc   +1 more source

Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses

Advanced Electronic Materials, EarlyView.
Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol, Nikhil Garg, Matteo Mazza, Yanming Zhang, Elisa Zaccaria, Wooseok Choi, Bert Jan Offrein, Laura Bégon‐Lours   +7 more
wiley   +1 more source

DINO-EYE: self-supervised learning for identification of different optic disc phenotypes in primary open angle glaucoma. [PDF]

Sci Rep
Grassi L, Fei Z, Morales E, Caprioli J.
europepmc   +1 more source

A Dual‐Memory Ferroelectric Transistor Emulating Synaptic Metaplasticity for High‐Speed Reservoir Computing

Advanced Electronic Materials, EarlyView.
A CMOS‐compatible ferroelectric transistor harnesses the interplay between stable gate polarization memory and volatile non‐quasi‐static channel charge dynamics to emulate how biological synapses regulate their own plasticity. This brain‐inspired dual‐memory mechanism, realized in a single device, enables a physical reservoir computer that solves ...
Yifan Wang, Muhammad Sakib Shahriar, Salma Soliman, Noah Vaillancourt, Lance Fernandes, Andrea Padovani, Asif Islam Khan, Md Sakib Hasan, Raisul Islam   +8 more
wiley   +1 more source

EVA-X: a foundation model for general chest x-ray analysis with self-supervised learning. [PDF]

NPJ Digit Med
Yao J, Wang X, Song Y, Zhao H, Ma J, Chen Y, Liu W, Wang B.   +7 more
europepmc   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee, Zachary T. Gossage, Shinichi Kumakura, Shinichi Komaba   +3 more
wiley   +1 more source

A foundation transformer model with self-supervised learning for ECG-based assessment of cardiac and coronary function. [PDF]

NEJM AI
Moody JB, Poitrasson-Rivière A, Renaud JM, Hagio T, Alahdab F, Al-Mallah MH, Vanderver MD, Goonewardena SN, Ficaro EP, Murthy VL.   +9 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