LLMs can identify major depressive disorder via voice note recordings

A new medical large language model (LLM) achieved over 91% accuracy in identifying female participants diagnosed with major ...

Pharmacy professor develops AI model to predict hospitalization of at-risk cardiac patients

When Arinze Nkemdirim Okere, PharmD, MBA, worked as the pharmacist for a hospital in Tallahassee, Florida, he noticed that ...
IEEE

EffNet-SVM: A Hybrid Model for Diabetic Retinopathy Classification Using Retinal Fundus Images

Abstract: The manual diagnosis of diabetic retinopathy (DR) is often invasive, time-consuming, expensive, and prone to human error. Additionally, it can be subjective ...
Frontiers

Development of a machine learning-based risk prediction model for early-stage pneumoconiosis: a retrospective study

Background: The diagnosis of occupational pneumoconiosis requires more accurate predictive models. The purpose of this study is to screen blood markers associated with early pneumoconiosis development ...
Frontiers

Machine learning-based prediction of occupational exposure risks among oral healthcare workers

Objective: This study aims to identify the key risk factors for occupational exposure among oral healthcare workers and develop a predictive model using machine learning algorithms to lay the ...
IEEE

Deep Flower: A Deep Learning Approach for Accurate Flower Classification

Abstract: Flower classification is a challenging task in computer vision, requiring models to discern subtle visual differences among a vast array of floral species. In this project, we propose a ...