Journal Basic Info

  • Impact Factor: 0.285**
  • H-Index: 6
  • ISSN: 2638-4558
  • DOI: 10.25107/2638-4558
**Impact Factor calculated based on Google Scholar Citations. Please contact us for any more details.

Major Scope

  •  Epilepsy and Seizures
  •  Allergy & Immunology
  •  Physiology
  •  Physiotherapy
  •  Geriatric Medicine
  •  Traumatology
  •  Obstetrics and Gynecology
  •  Urology Cases

Abstract

Citation: Clin Case Rep Int. 2024;8(1):1670.DOI: 10.25107/2638-4558.1670

Enhancing Infectious Disease Management in Nigeria: The Role of Artificial Intelligence in Diagnosis and Treatment

Ajayi OO, Wright-Ajayi B, Mosaku LA, Davies GK, Moneke KC, Adeleke OR, Shaba DS and Mudele O

Department of Sustainability and Social Justice, Clark University, USA
Ireti Resource Center, Programs Section, Women’s Rights and Health Project (WRAHP), Nigeria
School of Public Health, University of Illinois at Springfield, USA
Department of Nutrition, Harvard University, USA

*Correspondance to: Oluwole Olakunle Ajayi 

 PDF  Full Text Review Article | Open Access

Abstract:

Infectious diseases present major obstacles to global public health systems, especially in resourcepoor areas like Nigeria. Artificial Intelligence (AI) methods for disease detection, medication development, and patient risk assessment are widely used in healthcare. In the low-resource setting like what Nigeria represents, the benefits of AI in offsetting major systemic and resource constraints cannot be overemphasized. In light of the recent strides by the Nigerian government to support local AI adoption and talent development, we present an overview of how public and private health management and delivery practitioners should being to think about adopting AI technologies to improve health services delivery within the country, especially towards managing infectious diseases. Our overview is based on a mixture of on-the ground experience and literature studies. With the evidence in literature showing that AI shows great promise for enhancing clinical laboratory testing, disease diagnosis, and treatment selection, we have argued that by prioritizing AI integration into health systems in Nigeria, there will be higher accuracy in diagnoses, lower costs of service provision, and time savings to ensure the understaffed health systems can reach more people.

Keywords:

Infectious disease; Nigeria; Machine learning; Artificial intelligence

Cite the Article:

Ajayi OO, Wright-Ajayi B, Mosaku LA, Davies GK, Moneke KC, Adeleke OR, et al. Enhancing Infectious Disease Management in Nigeria: The Role of Artificial Intelligence in Diagnosis and Treatment. Clin Case Rep Int. 2024; 8: 1670.

Search Our Journal

Journal Indexed In

Articles with Grants

Multidisciplinary Approach to Scheduling Surgery for Diabetic Foot: A Case Report
 Abstract  PDF  Full Text
Clinicopathological Characteristics of Medullary Thyroid Carcinoma with the Expression of Thyroglobulin in East – China
 Abstract  PDF  Full Text
View More...