Results 241 to 250 of about 320,245 (358)

Biomarker‐Agnostic Detection of Ovarian Cancer from Blood Plasma Using a Machine Learning‐Driven Electronic Nose

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a biomarker‐agnostic diagnostic strategy for ovarian cancer, utilizing a machine learning‐enhanced electronic nose to analyze volatile organic compound signatures from blood plasma. By overcoming the dependence on specific biomarkers, this approach enables accurate detection, staging, and cancer type differentiation, offering a ...
Ivan Shtepliuk   +4 more
wiley   +1 more source

Predicting Materials Thermodynamics Enabled by Large Language Model‐Driven Dataset Building and Machine Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
Illustration of text data mining of rare earth mineral thermodynamic parameters with the large language model‐powered LMExt. A dataset is built with mined thermodynamic properties. Subsequently, a machine learning model is trained to predict formation enthalpy from the dataset.
Juejing Liu   +6 more
wiley   +1 more source

Reasoning-based LLMs surpass average human performance on medical social skills. [PDF]

open access: yesSci Rep
Alohali KI   +4 more
europepmc   +1 more source

Iterative Data Curation for Machine Learning‐Based Inverse Design of Active Composite Plates for Four‐Dimensional Printing

open access: yesAdvanced Intelligent Systems, EarlyView.
A machine learning framework is developed for the inverse design of 4D‐printed active composite plates. It utilizes a forward model to predict shapes from patterns and an inverse model to suggest initial patterns for desired shapes. This framework integrates a genetic algorithm to refine the predicted patterns, ensuring higher accuracy in achieving ...
Teerapong Poltue   +4 more
wiley   +1 more source

A CFIR-guided qualitative study of digital health engagement among Black adults with type 2 diabetes. [PDF]

open access: yesNPJ Digit Med
El Zein A   +7 more
europepmc   +1 more source

Upsampling DINOv2 Features for Unsupervised Vision Tasks and Weakly Supervised Materials Segmentation

open access: yesAdvanced Intelligent Systems, EarlyView.
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty   +2 more
wiley   +1 more source

Community perceptions and practices on hepatic veno-occlusive disease in Tigray, Ethiopia: An explorative study challenging the attribution to Ageratum conyzoides. [PDF]

open access: yesPLoS Negl Trop Dis
Haileselassie M   +24 more
europepmc   +1 more source

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