How well do frozen foundation models transfer? A calibration-focused benchmark for diabetic retinopathy grading. [PDF]
Poyrazer M, Yağcı H, Erten R.
europepmc +1 more source
Receptogenesis in a Vascularized Robotic Embodiment
Functional augmentation of situated robots via ex novo hardware generation extends physical adaptability. Drawing inspiration from open circulatory systems for mass and function redistribution, this study presents a vascularized robotic composite exhibiting receptogenesis ‐ the on‐demand construction of sensors ‐ from internal fluid reserves based on ...
Kadri‐Ann Pankratov +8 more
wiley +1 more source
Maternal Iodine Status During Pregnancy and Child Neurodevelopment: A Systematic Review and Dose-Response Meta-Analysis of Prospective Cohort Studies. [PDF]
Luo Q +7 more
europepmc +1 more source
Neuromorphic Devices and Computing for Sensing, Memory, and Control
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu +2 more
wiley +1 more source
Generative AI use and social disparities in pediatric rehabilitation: a cross-sectional study of ChatGPT use among parents of children with speech and language disorders in Türkiye. [PDF]
Şimşek A, Güneş Z.
europepmc +1 more source
Conformal Reconfigurable Intelligent Surfaces: A Cylindrical Geometry Perspective
Cylindrical reconfigurable intelligent surfaces are explored for low‐complexity beam steering using one‐bit meta‐atoms. A multi‐level modeling approach, including optimization‐based synthesis, demonstrates that even minimal hardware can support directive scattering.
Filippo Pepe +4 more
wiley +1 more source
Evaluating large language models for accuracy incentivizes hallucinations. [PDF]
Kalai AT, Nachum O, Vempala SS, Zhang E.
europepmc +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
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 +6 more
wiley +1 more source
Evidence Mapping of ctDNA Reporting in Pancreatic Ductal Adenocarcinoma: Toward a Shared Quantitative Language for ctDNA. [PDF]
Croagh D, Aslani S.
europepmc +1 more source
On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels +4 more
wiley +1 more source

