Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Results: We evaluated the performance of the models by comparing predicted sentiments (either positive or negative) with the labels judged by human evaluators in terms of the aforementioned 3 aspects.

Abstract: Currently, existing garbage image classification models predominantly operate on low-end devices and encounter significant challenges, including limitations in computing resources, storage ...

Operating System: Ubuntu 20.04 Python Version: 3.8 GPU: 1x NVIDIA RTX 3090 with CUDA version 12.2 ...

What happens when you combine an Arduino-based microcontroller with a palm-sized aluminum box and clicky buttons? A fidget ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...