Results 91 to 100 of about 274,965 (227)

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
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

Ambiguity and free will: the topology of decision in quantum and quantum-like sciences. [PDF]

Philos Trans A Math Phys Eng Sci
Plotnitsky A.
europepmc   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

An effective deep learning algorithm for medical image registration. [PDF]

PLOS Digit Health
Deng J, Chen K, Li M, Zuo Z, Frangi AF, Zhang J.   +5 more
europepmc   +1 more source

Mathematical aspects of spin-momentum locking : generalization to magnonic systems and application of orbifold to topological material science

Mathematical aspects of spin-momentum locking : generalization to magnonic systems and application of orbifold to topological material science
学位の種別: 課程博士 審査委員会委員 : （主査）東京大学准教授 桂 法弥, 東京大学教授 大谷 義近, 東京大学教授 常行 真司, 東京大学教授 髙木 英典, 東京工業大学教授 村上 ...
openaire  

Adversarial Erasing Enhanced Multiple Instance Learning (siMILe): Discriminative Identification of Oligomeric Protein Structures in Single Molecule Localization Microscopy

Advanced Intelligent Systems, EarlyView.
Hallgrimson et al. introduce a machine learning algorithm, siMILe, that takes features of single‐molecule localization microscopy localization clusters (e.g., size and sphericity) and finds the clusters that are associated with certain cell conditions (such as differential protein expression or drug treatment).
Christian Hallgrimson, Y. Lydia Li, Claire A. Shou, Ben Cardoen, John Lim, Timothy H. Wong, Ismail M. Khater, Ivan Robert Nabi, Ghassan Hamarneh   +8 more
wiley   +1 more source

3D epithelial cell topology tunes signaling range to promote precise patterning. [PDF]

Proc Natl Acad Sci U S A
Paci G, Berkemeier F, Baum B, Page KM, Mao Y.   +4 more
europepmc   +1 more source

i‐Tac: Inverse Design of 3D‐Printed Tactile Elastomers with Tuneable Optical and Mechanical Properties

Advanced Intelligent Systems, EarlyView.
Inspired by the multi‐tissue architecture of the human fingertip dermis (A), this work introduces a mixture design using three PolyJet materials (AC/TM/GM) to expand the achievable elastomer property space (B). An inverse design pipeline (i‐Tac) is developed to map target optical/mechanical requirements to optimal material compositions (C), enabling ...
Wen Fan, Dandan Zhang
wiley   +1 more source

Ketazine‐Linked Covalent Organic Framework for Metal‐Free Electrocatalytic Nitrate‐to‐Ammonia Conversion

Angewandte Chemie, EarlyView.
A metal‐free fluorinated ketazine‐linked COF is introduced as an efficient electrocatalyst for nitrate reduction to ammonia under neutral conditions. Fluorine substitution enhances π–π stacking and crystallinity, enabling a Faradaic efficiency of 59.9% and an NH3 yield rate of 1639.9 µmol h−1 mgCOF−1 at −0.9 V versus RHE. This establishes an unexplored
Islam E. Khalil, Ashadul Adalder, Badr Elkamash, Narad Barman, Darosch Asgari, Luoxing Xiang, Warisha Tahir, Franziska Hess, Ranjit Thapa, Adisak Boonchun, Uttam Kumar Ghorai, Prasenjit Das, Arne Thomas   +12 more
wiley   +2 more sources

A Dataset of Benchmark Boolean Models for Gene Regulatory Networks. [PDF]

Sci Data
Hotstegs CLO, Llano JP, Kestler HA.
europepmc   +1 more source