Advancing plant metabolic research by using large language models to expand databases and extract labeled data. [PDF]
Knapp R, Johnson B, Busta L.
europepmc +1 more source
Next‐generation proteomics improves lung cancer risk prediction
This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj +4 more
wiley +1 more source
Ranking and Combining Latent Structured Predictive Scores without Labeled Data. [PDF]
Afshar S, Chen Y, Han S, Lin Y.
europepmc +1 more source
Exploiting unlabeled data in few-shot learning with manifold similarity and label cleaning
Michalis Lazarou +2 more
openalex +1 more source
Data and code for "A Linear Time Solution to the Labeled Robinson-Foulds Distance Problem"
Samuel Briand +3 more
openalex +1 more source
Developing a User-Centric Data Labelling Tool for Sentiment Analysis : A Comparative Study of Explainable AI and Non-Explainable AI [PDF]
Davies, Clare
openalex
Exploiting metabolic adaptations to overcome dabrafenib treatment resistance in melanoma cells
We show that dabrafenib‐resistant melanoma cells undergo mitochondrial remodeling, leading to elevated respiration and ROS production balanced by stronger antioxidant defenses. This altered redox state promotes survival despite mitochondrial damage but renders resistant cells highly vulnerable to ROS‐inducing compounds such as PEITC, highlighting redox
Silvia Eller +17 more
wiley +1 more source
Persistent Laplacian-enhanced algorithm for scarcely labeled data classification. [PDF]
Bhusal G, Merkurjev E, Wei GW.
europepmc +1 more source
TRAINING DATA SELECTION AND LABELING FOR MACHINE LEARNING BRAILLE RECOGNITION MODELS
Akmal Akhatov Shokh Abbos Ulugmurodov
openalex +1 more source

