Lower-performing countries follow a different pattern. Gains in basic infrastructure, water access, or food availability can raise SDG scores even when education systems, innovation capacity, or ...
Twenty-five years of research into complex systems shows why artificial intelligence will always produce errors in healthcare ...
In the past decade, AI’s success has led to uncurbed enthusiasm and bold claims – even though users frequently experience its ...
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 ...
Abstract: Depression is a significant mental health problem and presents a challenge for the machine learning field in the detection of this illness. This study explores automated depression ...
Abstract: E-health sensors and wearables play an important role in the detection and classification of many chronic diseases. A chronic disease requires active monitoring and its severity increases ...
Objective: To explore the construction and clinical visualization application of a mortality risk prediction model for sepsis patients based on an improved machine learning model. Methods: This ...
1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
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