Results 161 to 170 of about 20,406 (258)

Current Status and Challenges of Imaging‐Based Diagnosis of Lymph Node Metastasis in Colon Cancer: The Lymph Node Committee of the Japanese Society for Cancer of the Colon and Rectum

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
This review of the status and challenges of diagnosis of lymph node metastasis in colon cancer suggests that it is currently difficult to establish strict criteria for lymph node metastasis, indicating only moderate diagnostic performance. ABSTRACT Background Accurate pre‐treatment evaluation of lymph node metastasis (LNM) in colon cancer is important ...
Shimpei Ogawa   +4 more
wiley   +1 more source

A review of artificial intelligence in healthcare supply chains: untapped potential? [PDF]

open access: yesBMC Health Serv Res
Espinosa O   +5 more
europepmc   +1 more source

Dictionary‐based weak‐form training for noise‐robust series hybrid models with multiplicative unknowns

open access: yesAIChE Journal, EarlyView.
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho   +4 more
wiley   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

open access: yesAdvanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz   +2 more
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

open access: yesAdvanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour   +5 more
wiley   +1 more source

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