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The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification
Binary classification is a common task for which machine learning and computational
statistics are used, and the area under the receiver operating characteristic curve (ROC …
statistics are used, and the area under the receiver operating characteristic curve (ROC …
Ten quick tips for avoiding pitfalls in multi-omics data integration analyses
Data are the most important elements of bioinformatics: Computational analysis of
bioinformatics data, in fact, can help researchers infer new knowledge about biology …
bioinformatics data, in fact, can help researchers infer new knowledge about biology …
Ten quick tips for electrocardiogram (ECG) signal processing
The electrocardiogram (ECG) is a powerful tool to measure the electrical activity of the heart,
and the analysis of its data can be useful to assess the patient's health. In particular, the …
and the analysis of its data can be useful to assess the patient's health. In particular, the …
Machine learning approach using 18F-FDG-PET-radiomic features and the visibility of right ventricle 18F-FDG uptake for predicting clinical events in patients with …
M Nakajo, D Hirahara, M **guji, S Ojima… - Japanese Journal of …, 2024 - Springer
Objectives To investigate the usefulness of machine learning (ML) models using
pretreatment 18F-FDG-PET-based radiomic features for predicting adverse clinical events …
pretreatment 18F-FDG-PET-based radiomic features for predicting adverse clinical events …
Robust cardiac segmentation corrected with heuristics
Cardiovascular diseases related to the right side of the heart, such as Pulmonary
Hypertension, are some of the leading causes of death among the Mexican (and worldwide) …
Hypertension, are some of the leading causes of death among the Mexican (and worldwide) …
Application of Machine Learning Analyses Using Clinical and [18F]-FDG-PET/CT Radiomic Characteristics to Predict Recurrence in Patients with Breast Cancer
K Kawaji, M Nakajo, Y Shinden, M **guji… - Molecular Imaging and …, 2023 - Springer
Purpose To develop and identify machine learning (ML) models using pretreatment clinical
and 2-deoxy-2-[18F] fluoro-d-glucose positron emission tomography ([18F]-FDG-PET) …
and 2-deoxy-2-[18F] fluoro-d-glucose positron emission tomography ([18F]-FDG-PET) …
Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [18F]-FDG-PET-radiomic features
M Nakajo, D Hirahara, M **guji, T Idichi… - Japanese Journal of …, 2024 - Springer
Objectives This study evaluates the effectiveness of machine learning (ML) models that
incorporate clinical and 2-deoxy-2-[18 F] fluoro-D-glucose ([18 F]-FDG)-positron emission …
incorporate clinical and 2-deoxy-2-[18 F] fluoro-D-glucose ([18 F]-FDG)-positron emission …
Applying deep learning-based ensemble model to [18F]-FDG-PET-radiomic features for differentiating benign from malignant parotid gland diseases
M Nakajo, D Hirahara, M **guji, M Hirahara… - Japanese Journal of …, 2024 - Springer
Objectives To develop and identify machine learning (ML) models using pretreatment 2-
deoxy-2-[18F] fluoro-D-glucose ([18F]-FDG)-positron emission tomography (PET)-based …
deoxy-2-[18F] fluoro-D-glucose ([18F]-FDG)-positron emission tomography (PET)-based …
[PDF][PDF] Machine Learning Analysis of Predictors for Inhaled Nitric Oxide Therapy Administration Time Post Congenital Heart Disease Surgery: A Single-Center …
S Niiyama, T Nakashima, K Ueno, D Hirahara… - Cureus, 2024 - cureus.com
Background Congenital heart disease (CHD) is a structural deformity of the heart present at
birth. Pulmonary hypertension (PH) may arise from increased blood flow to the lungs …
birth. Pulmonary hypertension (PH) may arise from increased blood flow to the lungs …
Machine learning based prediction model for acute coronary syndrome using biomarker
S Hajare, R Rewatkar, KTV Reddy - AIP Conference Proceedings, 2024 - pubs.aip.org
Cardio-vascular diseases, particularly acute coronary disease, remain a leading cause of
mortality worldwide. Timely and accurate prediction of heart disease risk is essential for …
mortality worldwide. Timely and accurate prediction of heart disease risk is essential for …