A Language‐Guided Multimodal Foundation Model for Zero‐Shot and Multi‐Task Brain Signal Analysis
METIS aligns brain signals with natural‐language instructions to enable zero‐shot and multi‐task brain signal analysis. Pretrained on over 70 000 h of EEG and iEEG recordings, it generalizes across sleep stage classification, epilepsy detection, and neurological disorder diagnosis, providing a scalable foundation model for clinically meaningful brain ...
Mingzhi Chen +3 more
wiley +1 more source
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha +2 more
wiley +1 more source
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez +3 more
wiley +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
Empirical PK/PD Model for Differentiating Intrinsic Dosing Rules by Therapeutic Indication With Relevance for HIV-1 Latency Reversal. [PDF]
Tompkins LAR +7 more
europepmc +1 more source
Inspired by human touch, a tendon‐driven soft robotic finger combines multimodal tactile sensing and deep learning to simultaneously perceive texture and softness on deformable surfaces. A CNN‐LSTM model fuses pressure, accelerometer, and gyroscope signals to accurately classify material properties, achieving up to 95.4% texture and 97.0% softness ...
Gorkem Anil Al +3 more
wiley +1 more source
A two‐terminal IGZO memtransistor enabling low‐voltage operation is demonstrated through coupling enhancement. By utilizing drain‐induced Fowler–Nordheim tunneling, the device achieves programming below 10 V with a large memory window and high on/off ratio.
Junhyeong Park +5 more
wiley +1 more source
A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe +9 more
wiley +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Selection of effective LRAs using a newly designed <i>in vitro</i> HIV latency reactivation protocol: toward future application in HIV samples. [PDF]
Neri A +14 more
europepmc +1 more source

