Results 161 to 170 of about 2,974 (234)

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

AI-Powered Workflow for Constructing Organic Materials Databases from the Literature: Integrating Large Language Models. [PDF]

ACS Omega
Hu H, Stirrat HJ, Alayli A, Saeki A, Huang Y.   +4 more
europepmc   +1 more source

Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage

Advanced Intelligent Discovery, EarlyView.
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, Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Thi Hong Nhung Vu, Sung Ha Park   +5 more
wiley   +1 more source

A framework for normalized extraction of fine-grained traditional Chinese medicine symptom entities and relations. [PDF]

BMC Med Inform Decis Mak
Gou X, Yao J, Lai W, Gao Y, Wang S, Zhou C, Ye H, Tian J, Yi J, Cao D.   +9 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

On the Utilization and Characterization of External Biotransformation Systems in <i>In Vitro</i> Toxicology: A Critical Review of the Scientific Literature with Guidance Recommendations. [PDF]

ACS Environ Au
Lungu-Mitea S, Stein Åslund M, Reichstein I, Pinto-Vidal FA, Schiwy A, Hollert H, Jacobs MN, Hilscherová K.   +7 more
europepmc   +1 more source

Revealing Protein–Protein Interactions Using a Graph Theory‐Augmented Deep Learning Approach

Advanced Intelligent Discovery, EarlyView.
This study presents a fast, cost‐efficient approach for classifying protein–protein interactions by integrating graph‐theory parametrization with deep learning (DL). Multiscale features extracted from graph‐encoded polarized‐light microscopy (PLM) images enable accurate prediction of binding strengths.
Bahar Dadfar, Gözde Kabay, Matthias Franzreb, Kody Whisnant, Nicholas A. Kotov, Joerg Lahann   +5 more
wiley   +1 more source

Interpretable clinical decision support systems in high-risk pregnancy: a scoping review of models, methods, and implementation. [PDF]

BMC Pregnancy Childbirth
Badisy IE, Assarag B, Belrhiti Z.
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

A hybrid deep learning and fuzzy logic framework for feature-based evaluation of english Language learners. [PDF]

Sci Rep
Zhao X.
europepmc   +1 more source