Results 201 to 210 of about 16,504,576 (273)

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Automated Large-Scale Extraction of Nanotoxicity Data from the Literature Using Multimodal Large Language Models. [PDF]

Comput Struct Biotechnol J
Park SG, Ha SM, Gerelkhuu Z, Yoon TH.
europepmc   +1 more source

Exploring Multi-Grained Concept Annotations for Multimodal Large Language Models

Multimodal Large Language Models (MLLMs) excel in vision--language tasks by pre-training solely on coarse-grained concept annotations (e.g., image captions). We hypothesize that integrating fine-grained concept annotations (e.g., object labels and object
Kan, Min-Yen, Xu, Xiao, Qin, Libo, Che, Wanxiang, Xie, Yuxi, Niu, Tianhao   +5 more
core  

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

Voice-controlled super-resolution ultrasound imaging and reporting powered by multimodal large language models. [PDF]

NPJ Digit Med
Guo N, Deng Z, Tan Q, Sheng K, Wang X, Wang S, Hua C.   +6 more
europepmc   +1 more source

AI Powered Biobanks From Static Archives to Dynamic Discovery Engines

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) provide a potential framework for transforming biobanks from static data repositories into intelligent discovery engines. By enabling unified representation and analysis of multimodal biomedical data, LLM‐based systems facilitate dynamic risk prediction, biomarker identification, and mechanistic interpretation, thereby ...
Wenzhen Yin, Yutian Feng, Wenrui Ma, Yuxin Su, Li Min, Juan Liu   +5 more
wiley   +1 more source

A Bilingual Benchmark for Evaluating Diagnostic Performance of Multimodal Large Language Models in Radiology (RadM-Bench): Evaluation Development and Validation. [PDF]

J Med Internet Res
Wu Q, Wu Q, Zhang P, Yi Z, Shen Y, Bai Y, Tan H, Dong P, Xue Z, Roberts N, Wang M.   +10 more
europepmc   +1 more source

Mastering Transformers: The Journey from BERT to Large Language Models and Stable Diffusion

Transformer-based language models such as BERT, T5, GPT, DALL-E, and ChatGPT have dominated NLP studies and become a new paradigm. Thanks to their accurate and fast fine-tuning capabilities, transformer-based language models have been able to outperform ...
Yıldırım, Savaş, Asgari-Chenaghlu, Meysam   +1 more
core  

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

Multimodal Large Language Models for Prognostic Prediction in Cervical Cancer Treated with Definitive Chemoradiotherapy: An Exploratory Study of Systematic Multimodal Data Integration. [PDF]

Cancers (Basel)
Gu Z, Wang C, Zhu Q, Wang W, Zhang Y, Hu K.   +5 more
europepmc   +1 more source