ARTÍCULO
TITULO

Artificial Intelligence in Pharmaceutical and Healthcare Research

Subrat Kumar Bhattamisra    
Priyanka Banerjee    
Pratibha Gupta    
Jayashree Mayuren    
Susmita Patra and Mayuren Candasamy    

Resumen

Artificial intelligence (AI) is a branch of computer science that allows machines to work efficiently, can analyze complex data. The research focused on AI has increased tremendously, and its role in healthcare service and research is emerging at a greater pace. This review elaborates on the opportunities and challenges of AI in healthcare and pharmaceutical research. The literature was collected from domains such as PubMed, Science Direct and Google scholar using specific keywords and phrases such as ?Artificial intelligence?, ?Pharmaceutical research?, ?drug discovery?, ?clinical trial?, ?disease diagnosis?, etc. to select the research and review articles published within the last five years. The application of AI in disease diagnosis, digital therapy, personalized treatment, drug discovery and forecasting epidemics or pandemics was extensively reviewed in this article. Deep learning and neural networks are the most used AI technologies; Bayesian nonparametric models are the potential technologies for clinical trial design; natural language processing and wearable devices are used in patient identification and clinical trial monitoring. Deep learning and neural networks were applied in predicting the outbreak of seasonal influenza, Zika, Ebola, Tuberculosis and COVID-19. With the advancement of AI technologies, the scientific community may witness rapid and cost-effective healthcare and pharmaceutical research as well as provide improved service to the general public.

 Artículos similares

       
 
Thoralf Reis, Lukas Dumberger, Sebastian Bruchhaus, Thomas Krause, Verena Schreyer, Marco X. Bornschlegl and Matthias L. Hemmje    
Manual labeling and categorization are extremely time-consuming and, thus, costly. AI and ML-supported information systems can bridge this gap and support labor-intensive digital activities. Since it requires categorization, coding-based analysis, such a... ver más

 
Davy Preuveneers and Wouter Joosen    
Ontologies have the potential to play an important role in the cybersecurity landscape as they are able to provide a structured and standardized way to semantically represent and organize knowledge about a domain of interest. They help in unambiguously m... ver más
Revista: Future Internet

 
Muhammad Sher Ramzan, Anees Asghar, Ata Ullah, Fawaz Alsolami and Iftikhar Ahmad    
The Internet of Things (IoT) consists of complex and dynamically aggregated elements or smart entities that need decentralized supervision for data exchanging throughout different networks. The artificial bee colony (ABC) is utilized in optimization prob... ver más
Revista: Future Internet

 
Zhengyang Fan, Wanru Li, Kathryn Blackmond Laskey and Kuo-Chu Chang    
Phishing attacks represent a significant and growing threat in the digital world, affecting individuals and organizations globally. Understanding the various factors that influence susceptibility to phishing is essential for developing more effective str... ver más
Revista: Future Internet

 
Mahmoud Elkhodr, Samiya Khan and Ergun Gide    
In the modern digital landscape of the Internet of Things (IoT), data interoperability and heterogeneity present critical challenges, particularly with the increasing complexity of IoT systems and networks. Addressing these challenges, while ensuring dat... ver más
Revista: Future Internet