Applications of deep learning in healthcare, finance, agriculture, retail, energy, manufacturing, and transportation: A review
Nitin Liladhar Rane, Suraj Kumar Mallick, Ömer Kaya, Jayesh Rane
Abstract
Deep Learning (DL), a branch of Artificial Intelligence (AI), has transformed many sectors by allowing groundbreaking progress in automation, predictive analytics, and smart decision-making. In the manufacturing industry, DL algorithms improve quality control by detecting defects in real-time and predicting maintenance needs, ultimately decreasing downtime and operational expenses. The healthcare industry uses DL to enhance patient outcomes and operational efficiency through improved diagnostics, personalized treatment plans, and accelerated drug discovery. Within the finance sector, DL models are utilized for detecting fraud, executing algorithmic trading, and managing risks, delivering strong and precise financial analysis. The retail industry uses DL for advanced recommendation systems, inventory management, and customer sentiment analysis, which boosts sales and enhances customer satisfaction. Self-driving cars in the automotive sector depend on DL for immediate image recognition and decision-making, leading to safer and more effective transportation. In addition, the telecommunications sector utilizes DL for improving network performance, forecasting analytics, and enhancing customer satisfaction. Applications in crop monitoring, yield prediction, and pest detection in the agriculture sector encourage sustainable farming practices. The advancement of DL will lead to innovation, increased efficiency, and transformative growth in different sectors.