Artificial Intelligence in Healthcare: Insights into Medical Doctors' Knowledge, Perceptions, and Attitudes in Sokoto, Nigeria

Authors

Keywords:

Artificial intelligence, Attitude, Knowledge, Medical doctors, Perception

Abstract

Artificial intelligence is rapidly transforming many industries, and healthcare is one of the most promising areas. Its integration could fundamentally change how diseases are diagnosed, treated, and managed, as well as improve the overall operation and delivery of healthcare services worldwide. This study aimed to determine the knowledge, perception and attitude of medical doctors towards the use of Artificial intelligence. Using stratified sampling technique, we recruited medical doctors across all cadre of doctors in the clinical departments of Usmanu Danfodiyo University Teaching Hospital and Specialist Hospital in Sokoto, north-western Nigeria. Having obtained informed consent, the data was collected using self-administered questionnaires. It was then analyzed using SPSS V25 for windows and level of significance was set at p<0.05. Almost all (176, 98.9%) of the respondents have heard of artificial intelligence, but 50.0% never think it will reach clinical value. Also, (152, 85.4%) believed that AI will improve  healthcare and (66, 37.1%) believed AI would not consider emotional well-being. More than half (95, 53.4%) believed AI will lead to loss of job. In addition, (83, 46.6%) believed AI will improve the efficiency of their practice and (143, 80.3%) were willing to embrace AI if trained. There was no significant association between the age, years of experience and familiarization with Artificial intelligence among the participants. Medical doctors generally indicated good knowledge and perception towards the use of Artificial intelligence in healthcare. However, the attitude towards AI utilization among medical doctors was affected by lack of formal training and sensitization programs.

Author Biographies

  • Magaji BA, Usmanu Danfodiyo University

    Department of Community Health, Faculty of Clinical Sciences, College of Health Sciences, Usmanu Danfodiyo University, Sokoto Nigeria, and . 3
    One Health Institute, Usmanu Danfodiyo University, Sokoto Nigeria

  • Abubakar A, Usmanu Danfodiyo University

    Department of Psychiatry, Usmanu Danfodiyo University Teaching Hospital, Sokoto Nigeria. 

  • Garba JA, Usmanu Danfodiyo University

    Department of Obstetrics and Gynecology, Usmanu Danfodiyo University Teaching Hospital, Sokoto Nigeria.

  • Yakubu IA, Usmanu Danfodiyo University

    Department of Psychiatry, Usmanu Danfodiyo University Teaching Hospital, Sokoto Nigeria.

  • Suleiman UO, Usmanu Danfodiyo University

    Department of Community Health, Faculty of Clinical Sciences, College of Health Sciences, Usmanu Danfodiyo University, Sokoto Nigeria

  • Bello Y, Usmanu Danfodiyo University

    Department of Community Health, Faculty of Clinical Sciences, College of Health Sciences, Usmanu Danfodiyo University, Sokoto Nigeria

  • Ibrahim RU, Usmanu Danfodiyo University

    Department of Community Health, Faculty of Clinical Sciences, College of Health Sciences, Usmanu Danfodiyo University, Sokoto Nigeria

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Published

2025-04-19

Issue

Vol. 6 No. 2 (2025): Renal Resistivity Index and its Relationship with other markers of renal damage in Sickle Cell Disease

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Articles