Artificial Intelligence in Healthcare: A Focus on Chest X-ray Disease Detection

Atharv Singh

Keywords: Artificial Intelligence, AI, healthcare, chest X-ray, disease detection, deep learning, medical image analysis, radiology, diagnostic accuracy, clinical workflow, ethical considerations.

Abstract : Artificial Intelligence (AI) has emerged as a revolutionary force in healthcare, with the potential to transform diagnosis, treatment, and overall patient outcomes. This paper explores the growing applications of AI in healthcare, focusing specifically on its use in chest X-ray disease detection. The paper begins by providing an overview of AI and its various subfields, particularly deep learning, which plays a crucial role in medical image analysis. Deep learning, a subset of machine learning, leverages neural networks to model complex patterns and relationships in data, enabling highly accurate predictions and classifications.The application of AI in chest X-ray disease detection addresses several critical challenges in the medical field. Traditional chest X-ray interpretation often involves a significant workload burden on radiologists, leading to potential delays in diagnosis and treatment. Furthermore, human error remains a considerable risk, as even experienced radiologists can miss subtle indicators of disease due to fatigue or other factors. AI systems, on the other hand, can analyse vast amounts of data quickly and consistently, providing a valuable second opinion that can enhance diagnostic accuracy.This paper reviews current advancements in AI algorithms for chest X-ray analysis, highlighting key studies and technological innovations. It examines the integration of AI into clinical workflows, discussing the benefits of augmented decision-making for radiologists. The potential for AI to improve early detection of diseases such as pneumonia, tuberculosis, and lung cancer is also explored, emphasising its impact on patient outcomes and healthcare efficiency.Moreover, the paper addresses ethical considerations and the need for robust validation and regulation of AI systems in healthcare. Issues of data privacy, bias in AI algorithms, and the importance of maintaining human oversight in AI-assisted diagnoses are discussed. The future outlook for AI in chest X-ray disease detection is considered, with a focus on ongoing research, potential obstacles, and the anticipated evolution of AI capabilities.

Published Paper   E-Certificate

"Artificial Intelligence in Healthcare: A Focus on Chest X-ray Disease Detection", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.9, Issue 8, page no.124 - 127, August-2024, Available :https://ijsdr.org/papers/IJSDR2408015.pdf

Volume 9 Issue 8, August-2024

Pages : 124 - 127

Paper Reg. ID: IJSDR_212256

Published Paper Id: IJSDR2408015

Downloads: 000347397

Research Area: Computer Science & Technology 

Country: Ghaziabad, Uttar Pradesh, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2408015

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2408015

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition