… From the way we communicate to how we travel, work, and … The integration of Artificial
Intelligence (AI) into the agricultural … of antibiotics, addressing concerns of antibiotic resistance. …

… ⁃ ly understand the application of artificial intelligence in drug discovery, this … , finally discusses
the opportunities and challenges of AI in future drug … Identification of antibiotic resistance …

… the applications of machine learning and deep learning in AMP prediction, highlighting …
antibiotic resistance issues. Keywords: Artificial Intelligence, Deep Learning, Machine Learning, …

… solution to drug resistance in patients, which also provides a reference for the work of other
… study, including random forest (RF) 14, artificial neural network (ANN) 15, k-nearest neighbor …

… experiments remains a substantial challenge. Using a small … of artificial intelligence algorithms,
machine learning (ML) is … , with only 1152 data points used in this work. (2) The principles …

… and accurate diagnosis and prediction is rather challenging. The rapid development of
artificial intelligence (AI) in the imaging field offers hope for solving these clinical challenges. This …

… 利用人工智能(artificial intelligence, AI)技术进行MDR-TB的辅助诊断将成为未来一个新的
重点… ] Drug-resistant tuberculosis is a respiratory infectious disease caused by drugresistant …

… artificial intelligence a qualitative shift that affected the work … challenges in the engineering
of buildings remains management of environment and conditions due to many factors at work…

… Despite these ample opportunities, it remains challenging to … In this context, the emerging
artificial intelligence (AI) … A machine learning approach for predicting defluorination of Per-…

… Machine Learning, Artificial Intelligence (ML and AI) technologies for assessment of physiological
state of the model plant. These issues … factor discussed in this work and some others) …