Results 211 to 220 of about 6,131,436 (285)

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

An explainable unsupervised learning approach for anomaly detection on corneal <i>in vivo</i> confocal microscopy images. [PDF]

Front Bioeng Biotechnol
Tang N, Chen Q, Meng Y, Lei D, Jiang L, Qin Y, Huang X, Tang F, Huang S, Lan Q, Chen Q, Huang L, Lan R, Pan X, Wang H, Xu F, He W.   +16 more
europepmc   +1 more source

Where Tech Meets the SDGs: A Supply‐Chain Process Map for Sustainability Management

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study investigates how advanced technologies support Sustainable Development Goals (SDGs) within supply chain management (SCM) through a structured analysis of 4448 sustainable practices. By integrating perspectives from sustainability‐oriented innovation (SOI) and contingent dynamic capabilities, the research conceptualizes technology ...
Vincenzo Varriale, Antonello Cammarano, Moacir Godinho‐Filho   +2 more
wiley   +1 more source

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients. [PDF]

PLoS One
Hall JM, Xu J, Walsh MG, Cho HD, Harrell G, Keshwani SA, Smith SM, Staras SAS.   +7 more
europepmc   +1 more source

A Computational Workflow for Cell Line Profiling by Imaging Mass Cytometry

Cytometry Part A, EarlyView.
ABSTRACT In single‐cell spatial phenotyping biology, imaging mass cytometry (IMC) stands out as a cutting‐edge, highly multiplexed technology driving discoveries across various disease areas. In vitro profiling relies on tumor‐derived cancer cell lines, known for their diverse morphologies and phenotypes.
Alexandre Bouzekri, Amanda Esch, Olga Ornatsky   +2 more
wiley   +1 more source

Cross-device federated unsupervised learning for the detection of anomalies in single-lead electrocardiogram signals. [PDF]

PLOS Digit Health
Kapsecker M, Jonas SM.
europepmc   +1 more source

Automated CLL cell population detection using a weakly supervised approach and CLL MRD flow cytometry data

Cytometry Part B: Clinical Cytometry, EarlyView.
Abstract Minimal/measurable residual disease detection is routinely performed as part of post‐diagnostic treatment plans for many types of cancer, for which multiparameter flow cytometry is one possible modality frequently used. We propose a machine learning approach for binary prediction of minimal residual disease status with flow cytometry data. Our
Wikum Dinalankara, Chandler Sy, Jiani Chai, Paul B. Barone, Luigi Marchionni, Paul D. Simonson   +5 more
wiley   +1 more source

Unlocking the soundscape of coral reefs with artificial intelligence: pretrained networks and unsupervised learning win out. [PDF]

PLoS Comput Biol
Williams B, Balvanera SM, Sethi SS, Lamont TAC, Jompa J, Prasetya M, Richardson L, Chapuis L, Weschke E, Hoey A, Beldade R, Mills SC, Haguenauer A, Zuberer F, Simpson SD, Curnick D, Jones KE.   +16 more
europepmc   +1 more source

Real‐time monitoring of tunnel structures using digital twin and artificial intelligence: A short overview

Deep Underground Science and Engineering, EarlyView.
How artificial intelligence (AI) and digital twin (DT) technologies are revolutionizing tunnel surveillance, offering proactive maintenance strategies and enhanced safety protocols. It explores AI's analytical power and DT's virtual replicas of infrastructure, emphasizing their role in optimizing maintenance and safety in tunnel management.
Mohammad Afrazi, Danial Jahed Armaghani, Hossein Afrazi, Hadi Fattahi, Pijush Samui   +4 more
wiley   +1 more source

Identifying Novel Emotions and Wellbeing of Horses from Videos Through Unsupervised Learning. [PDF]

Sensors (Basel)
Bhave A, Kieson E, Hafner A, Gloor PA.
europepmc   +1 more source