Vascular tree tracking and bifurcation points detection in retinal images using a hierarchical probabilistic model
Sign Up to like & getrecommendations! Published in 2017 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2017.08.018
Abstract: BACKGROUND AND OBJECTIVE Retinal vascular tree extraction plays an important role in computer-aided diagnosis and surgical operations. Junction point detection and classification provide useful information about the structure of the vascular network, facilitating objective analysis… read more here.
Keywords: precision recall; hierarchical probabilistic; model; vascular tree ... See more keywords
A method for utilizing automated machine learning for histopathological classification of testis based on Johnsen scores
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-89369-z
Abstract: We examined whether a tool for determining Johnsen scores automatically using artificial intelligence (AI) could be used in place of traditional Johnsen scoring to support pathologists’ evaluations. Average precision, precision, and recall were assessed by… read more here.
Keywords: precision recall; average precision; johnsen scores; johnsen ... See more keywords
NeuroTutor: Neural Decoding of Student Engagement During Virtual and Robotic Tutoring
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3585826
Abstract: The use of electroencephalography (EEG)-based analysis in educational research offers valuable insight into the dynamics of virtual and robot-based tutoring systems. This study aims to classify neural patterns associated with two distinct tutoring modalities (virtual… read more here.
Keywords: tutoring modalities; accuracy precision; precision recall; eeg based ... See more keywords
Topological Alternatives for Precision and Recall in Generative Models
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3598704
Abstract: We introduce the Normalized Topological Divergence (NTD), a fully differentiable metric that simultaneously quantifies fidelity and diversity of generative models directly in raw pixel or spectrogram space, eliminating reliance on pretrained feature extractors. For two… read more here.
Keywords: alternatives precision; generative models; precision recall; topological alternatives ... See more keywords
Development of machine learning-based mpox surveillance models in a learning health system
Sign Up to like & getrecommendations! Published in 2025 at "Sexually Transmitted Infections"
DOI: 10.1136/sextrans-2024-056382
Abstract: Objectives This study aimed to develop robust machine learning (ML)-based and deep learning (DL)-based models capable of detecting mpox cases for surveillance efforts using clinical notes. Methods As part of a learning health system initiative,… read more here.
Keywords: precision; precision recall; surveillance; machine learning ... See more keywords
The Effect of Class Imbalance on Precision-Recall Curves
Sign Up to like & getrecommendations! Published in 2020 at "Neural Computation"
DOI: 10.1162/neco_a_01362
Abstract: In this note, I study how the precision of a binary classifier depends on the ratio r of positive to negative cases in the test set, as well as the classifier's true and false-positive rates.… read more here.
Keywords: precision recall; imbalance precision; class imbalance; effect class ... See more keywords
Inferring ECOG performance status (PS) using large language models in patients with advanced prostate cancer.
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Clinical Oncology"
DOI: 10.1200/jco.2025.43.5_suppl.136
Abstract: 136 Background: The ECOG performance status (PS) is a critical measure for evaluating functional capacity and determining clinical trial eligibility in patients with advanced prostate cancer. We aim to assess the capability of large language… read more here.
Keywords: oncology; ecog; precision recall; score ... See more keywords
A fast and robust artificial intelligence technique for wood knot detection
Sign Up to like & getrecommendations! Published in 2020 at "Bioresources"
DOI: 10.15376/biores.15.4.9351-9361
Abstract: This study reports the feasibility of using deep convolutional neural networks (CNN), for automatically detecting knots on the surface of wood with high speed and accuracy. A limited dataset of 921 images were photographed in… read more here.
Keywords: knot detection; precision recall; precision; wood ... See more keywords
Enhancing Unmanned Aerial Vehicle Object Detection via Tensor Decompositions and Positive–Negative Momentum Optimizers
Sign Up to like & getrecommendations! Published in 2025 at "Mathematics"
DOI: 10.3390/math13050828
Abstract: The current development of machine learning has advanced many fields in applied sciences and industry, including remote sensing. In this area, deep neural networks are used to solve routine object detection problems, satisfying the required… read more here.
Keywords: detection; positive negative; object detection; negative momentum ... See more keywords