Role of artificial intelligence in early diagnosis and treatment of infectious diseases

被引:5
作者
Srivastava, Vartika [1 ,2 ]
Kumar, Ravinder [3 ]
Wani, Mohmmad Younus [4 ]
Robinson, Keven [5 ]
Ahmad, Aijaz [1 ,5 ]
机构
[1] Univ Witwatersrand, Fac Hlth Sci, Sch Pathol, Dept Clin Microbiol & Infect Dis, ZA-2193 Johannesburg, South Africa
[2] Cleveland Clin, Lerner Res Inst, Dept Inflammat & Immun, Cleveland, OH USA
[3] Univ Tennessee, Coll Med, Dept Pathol, Hlth Sci Ctr, Memphis, TN USA
[4] Univ Jeddah, Coll Sci, Dept Chem, Jeddah 21589, Saudi Arabia
[5] Univ Pittsburgh, Med Ctr, Div Pulm Allergy Crit Care & Sleep Med, Dept Med, Pittsburgh, PA 15213 USA
关键词
Artificial intelligence; infectious diseases; early diagnosis; treatment; machine learning; NONPHARMACEUTICAL INTERVENTIONS; DRUG DESIGN; COVID-19; SYSTEM; IMPACT; FUTURE; MODEL; TUBERCULOSIS; PREDICTION; INFLUENZA;
D O I
10.1080/23744235.2024.2425712
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Infectious diseases remain a global health challenge, necessitating innovative approaches for their early diagnosis and effective treatment. Artificial Intelligence (AI) has emerged as a transformative force in healthcare, offering promising solutions to address this challenge. This review article provides a comprehensive overview of the pivotal role AI can play in the early diagnosis and treatment of infectious diseases. It explores how AI-driven diagnostic tools, including machine learning algorithms, deep learning, and image recognition systems, enhance the accuracy and efficiency of disease detection and surveillance. Furthermore, it delves into the potential of AI to predict disease outbreaks, optimise treatment strategies, and personalise interventions based on individual patient data and how AI can be used to gear up the drug discovery and development (D3) process.The ethical considerations, challenges, and limitations associated with the integration of AI in infectious disease management are also examined. By harnessing the capabilities of AI, healthcare systems can significantly improve their preparedness, responsiveness, and outcomes in the battle against infectious diseases.
引用
收藏
页码:1 / 26
页数:26
相关论文
共 221 条
[1]   Applications of Artificial Intelligence in Transport: An Overview [J].
Abduljabbar, Rusul ;
Dia, Hussein ;
Liyanage, Sohani ;
Bagloee, Saeed Asadi .
SUSTAINABILITY, 2019, 11 (01)
[2]   Using artificial intelligence for improving stroke diagnosis in emergency departments: a practical framework [J].
Abedi, Vida ;
Khan, Ayesha ;
Chaudhary, Durgesh ;
Misra, Debdipto ;
Avula, Venkatesh ;
Mathrawala, Dhruv ;
Kraus, Chadd ;
Marshall, Kyle A. ;
Chaudhary, Nayan ;
Li, Xiao ;
Schirmer, Clemens M. ;
Scalzo, Fabien ;
Li, Jiang ;
Zand, Ramin .
THERAPEUTIC ADVANCES IN NEUROLOGICAL DISORDERS, 2020, 13
[3]   Weather forecasting model using Artificial Neural Network [J].
Abhishek, Kumar ;
Singh, M. P. ;
Ghosh, Saswata ;
Anand, Abhishek .
2ND INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION, CONTROL AND INFORMATION TECHNOLOGY (C3IT-2012), 2012, 4 :311-318
[4]   Collateral Impact of Public Health and Social Measures on Respiratory Virus Activity during the COVID-19 Pandemic 2020-2021 [J].
Achangwa, Chiara ;
Park, Huikyung ;
Ryu, Sukhyun ;
Lee, Moo-Sik .
VIRUSES-BASEL, 2022, 14 (05)
[5]  
Agrebi S, 2020, ARTIFICIAL INTELLIGENCE IN PRECISION HEALTH: FROM CONCEPT TO APPLICATIONS, P415, DOI 10.1016/B978-0-12-817133-2.00018-5
[6]   Multi-Techniques for Analyzing X-ray Images for Early Detection and Differentiation of Pneumonia and Tuberculosis Based on Hybrid Features [J].
Ahmed, Ibrahim Abdulrab ;
Senan, Ebrahim Mohammed ;
Shatnawi, Hamzeh Salameh Ahmad ;
Alkhraisha, Ziad Mohammad ;
Al-Azzam, Mamoun Mohammad Ali .
DIAGNOSTICS, 2023, 13 (04)
[7]   Machine-Learning-Based Disease Diagnosis: A Comprehensive Review [J].
Ahsan, Md Manjurul ;
Luna, Shahana Akter ;
Siddique, Zahed .
HEALTHCARE, 2022, 10 (03)
[8]   Artificial Intelligence and technology in COVID Era: A narrative review [J].
Ahuja, Vanita ;
Nair, Lekshmi, V .
JOURNAL OF ANAESTHESIOLOGY CLINICAL PHARMACOLOGY, 2021, 37 (01) :28-34
[9]   A prospective prediction tool for understanding Crimean-Congo haemorrhagic fever dynamics in Turkey [J].
Ak, C. ;
Ergonul, O. ;
Gonen, M. .
CLINICAL MICROBIOLOGY AND INFECTION, 2020, 26 (01) :123.e1-123.e7
[10]   Spatiotemporal prediction of infectious diseases using structured Gaussian processes with application to Crimean-Congo hemorrhagic fever [J].
Ak, Cigdem ;
Ergonul, Onder ;
Sencan, Irfan ;
Torunoglu, Mehmet Ali ;
Gonen, Mehmet .
PLOS NEGLECTED TROPICAL DISEASES, 2018, 12 (08)