Results 221 to 230 of about 105,781,316 (298)

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Multi-omics analysis suggests ZDHHC18 as a potential risk factor for clear cell renal cell carcinoma linked to myeloid DC morphology. [PDF]

Discov Oncol
Guo A, Lu Y, Wang J, Jia Z, Yang J, Ning X.   +5 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
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, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

A commentary on: "CD33 drives cutaneous melanoma: mendelian randomization confirms causality, multi-omics and in vitro experiments reveal M2 macrophage polarization-mediated progression". [PDF]

Int J Surg
Sun X, Xu L, Ni S.
europepmc   +1 more source

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

Editorial to the Special Issue "Recent Advances in Optical Wireless Communications". [PDF]

Sensors (Basel)
Genoves Guzman B, Morales Céspedes M.
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

MIRAGE: Robust multi-modal architectures translate fMRI-to-image models from vision to mental imagery. [PDF]

PLoS Comput Biol
Kneeland R, Villanueva CKT, Chen T, Ojeda J, Khanna S, Xu J, Scotti PS, Naselaris T.   +7 more
europepmc   +1 more source

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

Identification and validation of plasma protein biomarkers as therapeutic targets in acute myeloid leukemia: an integrative multi-omics study. [PDF]

Front Immunol
Hu L, Luo Q, Liao Y, Zhai Z, Ding Y, Fei Y.   +5 more
europepmc   +1 more source