Results 121 to 130 of about 41,060,851 (256)
The possibilities for data mining from large text collections are virtually untapped. Text expresses a vast, rich range of information, but encodes this information in a form that is difficult to decipher automatically. Perhaps for this reason, there has
Marti A. Hearst
core +1 more source
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler +7 more
wiley +1 more source
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley +1 more source
Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets
An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh +4 more
wiley +1 more source
Text mining provides the automated means to manage information overload and overlook. By adding meaning to text, text mining techniques produce a much more structured analysis of textual knowledge than do simple word searches, and can provide powerful ...
Ananiadou, Sophia; id_orcid +1 more
core +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage
We propose an overlapping‐based majority‐voting method for DNA data storage error correction. By aligning multiple reads and choosing the most frequent base per position, it suppresses substitution errors without prior models. Validated on synthetic and real sequencing data, it achieves high‐fidelity, scalable, and cost‐effective reconstruction ...
Thi Bich Ngoc Nguyen +5 more
wiley +1 more source
AI Powered Biobanks From Static Archives to Dynamic Discovery Engines
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 +5 more
wiley +1 more source
Novel Lexicon Hierarchy Semantic Embedding for Domain Specific Text Mining
Presentation for the 2018 International Conference on Knowledge Management.
Zhang, Zhixiong, Han, Tao, Chen, Xiaoli
core
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 +4 more
wiley +1 more source

