Results 141 to 150 of about 8,068,470 (297)
Employing a digital single‐molecule activity tracker (dSMAT), this research demonstrates that high‐photon‐flux irradiation drives progressive oxidative scarring in polymerases. Unlike simple thermal denaturation, real‐time kinetic tracking dynamically visualizes enzymes degrading into multiple impaired subpopulations.
Anran Zheng +11 more
wiley +1 more source
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 +15 more
wiley +1 more source
Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature
A deep learning model analyzes cfRNA profiles extracted from the blood of OVCA patients. This innovative approach distinguishes OVCA from healthy controls with high accuracy. Crucially, it reliably predicts patient response to chemotherapy (sensitive versus resistant subgroups).
Qinhao Guo +14 more
wiley +1 more source
Liquid metal catalysts are widely assumed to promote high‐quality 2D growth. In this work, operando experiments and machine‐learning‐accelerated simulations show that hBN on Cu breaks this graphene‐derived expectation, where molten Cu promotes multilayer/3D growth, but re‐solidified single‐crystal Cu stabilizes monolayer formation.
Nikoo Ghanadan +17 more
wiley +1 more source
Eligibility flow and real‐world AMD burden in the UKB retinal imaging cohort and TMUEH external‐validation cohort. Overview of the ORBIT‐AMD architecture, integrating retinal representation pretraining, bilateral eye‐graph modeling and concept bottleneck learning to support ordered risk, bilateral context, interpretable lesion concepts, longitudinal ...
Xuehao Cui +3 more
wiley +1 more source
Semi-supervised Learning with Deep Generative Models
The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised learning one of the problems of significant practical importance in modern data analysis.
Kingma, D.P. +7 more
core
datamole-ai/active-semi-supervised-clustering 0.0.1
Active semi-supervised clustering algorithms for scikit ...
Jakub Švehla
core +1 more source
This schematic compares m‐Si degradation in liquid electrolyte and solid electrolyte systems. In liquid electrolyte, repeated cycling induces severe particle pulverization and thick, unstable SEI growth. In contrast, the solid electrolyte configuration suppresses interfacial reactions, enabling a thin, stable SEI and improved structural integrity ...
Seokjin Kim, Jeongwoo Kim, Jaekyung Sung
wiley +1 more source
Convex Multiview Semi-Supervised Classification
In many practical applications, there are a great number of unlabeled samples available, while labeling them is a costly and tedious process. Therefore, how to utilize unlabeled samples to assist digging out potential information about the problem is ...
Feiping Nie +5 more
core +1 more source
We constructed a brain‐targeted AFn‐DPZ nanodrug delivery system and identified EphB1 as its receptor on the blood‐brain barrier (BBB). This system facilitates drug transport across the BBB and thereby ameliorates cognitive impairment in Alzheimer's disease.
Shilin Wen +5 more
wiley +1 more source

