There has been an exponential growth in the application of AI in health and in pathology.
This is resulting in the innovation of deep learning technologies that are specifically aimed at …

Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …

Abstract The paper presents Imbalance-XGBoost, a Python package that combines the
powerful XGBoost software with weighted and focal losses to tackle binary label-imbalanced …

Deep neural networks (DNNs) that predict mutational status from H&E slides of cancers can
enable inexpensive and timely precision oncology. Although expert knowledge is reliable for …

Clinical efforts on precision medicine are driving the need for accurate diagnostic, new
prognostic and novel drug predictive assays to inform patient selection and stratification for …

The objective of this research is to build a “Whole Slide Images” classification system using
Convolutional Neural Network (CNN). This system is capable of classifying Thyroid tumors …

Increased aerobic glycolysis portends an unfavorable prognosis in thyroid cancer. The
metabolic reprogramming likely results from altered mitochondrial activity and may promote …

This paper explores the impact of reweighting the minority class of an imbalanced fraud
dataset on the performance of an XGBoost binary classifier. Classifier performance is …

Thyroid cancer is the most common endocrine malignancy, and accurately distinguishing
between benign and malignant thyroid tumors is crucial for developing effective treatment …

SPINT1, also known as HAI-1, is a Kunitz-type serine protease inhibitor that inhibits multiple
proteases including hepatocyte growth factor (HGF) activator and matriptase. SPINT1 has …