Results 211 to 220 of about 3,564,449 (254)

<i>metaKEGG</i>: A comprehensive algorithm package to visualize multi-omics pathway enrichment. [PDF]

Biochem Biophys Rep
Lazaratos M, Haacke N, Gaugel J, Ulz M, Bleimehl T, Täger J, Schürmann A, Vogel H.   +7 more
europepmc   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

A Machine Vision‐Guided Microphysiological Platform With Automated Microfluidics Enables Longitudinal Biomarker Monitoring and Emulation of Translationally Relevant Exposure Scenarios

Advanced Science, EarlyView.
A pneumatically actuated multi‐tissue microphysiological system is integrated with AI‐based machine vision and automatic sampling and replenishment systems. The platform allows for the emulation of translationally relevant long‐term pharmacokinetic exposure scenarios for multiple weeks while enabling longitudinal monitoring of response biomarkers ...
Jibbe Keulen, Yi Zhong, Laura Dangel, Sonia Youhanna, Reza Zandi Shafagh, Jinhye Ryu, Domnica‐Gabriela Gurau, Mathias Haag, Thomas E. Mürdter, Yingxin Liang, Iro Beligiani, Nicole Ziegler, Sabine Willems, Nayere Taebnia, Wouter van der Wijngaart, Volker M. Lauschke   +15 more
wiley   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

CohAlign: Predicting the first-order noise susceptibility of gradients in equivariant quantum neural networks. [PDF]

PLoS One
Ugail H, Howard N.
europepmc   +1 more source

A Generative Neuro‐Symbolic AI for Protein Sequence Design

Advanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne, Delphine Dessaux, Samuel Buchet, Lucie Barthe, Liza Ammar‐Khodja, Bessam Azizi, Valentin Durante, Gianluca Cioci, Simon de Givry, Alain Roussel, Luis F. Garcia‐Alles, Thomas Schiex, Sophie Barbe   +12 more
wiley   +1 more source

Multitask Deep Learning Model for Predicting Lymph Node Metastasis and Disease‐Free Survival From Cytology Images in Bladder Cancer: A Multicenter Study With Pan‐Cytology Validation

Advanced Science, EarlyView.
Through self‐supervised pretraining and supervised fine‐tuning on large‐scale cytology image datasets, CytoNet predicts lymph node metastasis and survival. Across independent cohorts, this multitask framework demonstrates robust performance, improves risk stratification beyond radiological assessment, and provides interpretable evidence to support ...
Guibin Hong, Fan Jiang, Ye Xie, Xiaowei Huang, Runnan Shen, Yun Wang, Mengyi Zhu, Haoxuan Wang, Hongkun Yang, Yanxiao Nie, Zhen Lin, Rui Chen, Nengtai Ouyang, Tianxin Lin, Shaoxu Wu   +14 more
wiley   +1 more source

BVLab-analyzer: a unified visual toolbox for terabyte-scale whole-brain cell detection, neuron reconstruction, and vascular network extraction. [PDF]

Front Neuroinform
Hu Y, Wang X, Sun P, Shen Y, Quan T.
europepmc   +1 more source