Results 211 to 220 of about 1,464,707 (244)
When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
Sharing digital health data responsibly: Balancing open science with participant privacy. [PDF]
Nebeker C, Samiei S, Kumar S.
europepmc +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang +16 more
wiley +1 more source
Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 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
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
Behaviorally Adaptive and Inclusive Advanced Driver‐Assistance Systems
Advanced driver‐assistance systems (ADASs) are mapped as evolving human‐centered, adaptive technologies linking sensing, driver monitoring, AR/HUD interfaces, patents, regulation, and inclusive design. The review identifies gaps in real‐world evidence, diverse‐driver validation, gaze metrics, and governance, outlining a roadmap for safer, behaviorally ...
Jana Skirnewskaja +2 more
wiley +1 more source
ViTAMIn‐O: Democratizing Computer Vision‐Based Machine Learning for Stem Cell Research
This study introduces a fully open generalist computer vision model for predicting the differentiation outcomes of stem cell‐based model systems, together with its code‐free deployment platform, ColabViTAMIn‐O. It is benchmarked against various architectures, datasets, and training protocols.
Ferhat Hamurcu +11 more
wiley +1 more source

