Litcius/Paper detail

Machine Learning Advancements in E-Health

Pankaj Bhambri, Alex Khang

2024Advances in medical diagnosis, treatment, and care (AMDTC) book series16 citationsDOI

Abstract

A technologically evolved environment confronts the healthcare business. However, machine learning (ML) technology could revolutionize patient care, diagnosis, and decision-making. This chapter examines machine learning advances that can be applied to e-health. It also discusses machine learning algorithms in predictive analytics, personalized medicine, and early disease diagnosis. The chapter also emphasizes how ML, medical robotics, and AI-assisted diagnostics may improve healthcare delivery. Machine learning advancements in electronic health (e-health) are studied through case studies and real-world applications to determine their practical applications. This chapter also tackles ethical issues and challenges in healthcare ML integration. Readers will understand how machine learning is changing e-health to provide more effective, individualized, and precise healthcare solutions. This exploration contributes to the conversation on incorporating advanced technology into healthcare, paving the way for digital healthcare's technological future.

Topics & Concepts

Computer sciencePsychologyMachine Learning in HealthcareArtificial Intelligence in HealthcareCOVID-19 diagnosis using AI