The concept of Artificial Intelligence (AI) centers on machines, particularly computer systems, which mimic human thought processes. This broad field covers numerous technologies capable of performing tasks that typically require human intelligence, such as acquiring knowledge, critical thinking, problem-solving, and understanding verbal communication [1], [2]. These technologies include machine learning, in which algorithms are trained to make classifications or predictions, uncovering insights into data without being explicitly programmed; deep learning, which involves neural networks with many layers of processing units, taking advantage of advances in computing power and improved training techniques to learn complex patterns in large amounts of data; and natural language processing, which enables understanding, interpretation, and generation of human language by a computer [3], [4], [5]. AI is a broad field in computer science; however, its applications extend beyond computer science and cover a diverse range of fields, including health care. It is a fast-growing interdisciplinary area with the potential to revolutionize approaches to problem-solving in different fields [6]. In the healthcare domain, AI plays an important role in the treatment of diseases and significantly reduces errors in diagnosis and patient monitoring [7]. The use of AI has witnessed a recent surge, transitioning from theoretical research to practical applications in many industries [8].
Developed countries have allocated considerable financial resources to the advancement of AI research, particularly in healthcare. In lower-income countries, such as Somalia, there is an absence of strategies for the adoption of AI, in addition to a lack of research focused on this technology [9]. In the past decade, AI domains have witnessed significant expansion in technological advancements. Despite the long-standing history of AI development across various uses, the current wave of AI excitement sets itself apart from previous periods. The rapid progress of AI tools and approaches in the healthcare sector has been enabled by a combination of enhanced computational processing abilities, extensive data storage facilities, and a wealth of expertise in artificial intelligence [10], [11].
However, AI, especially machine learning (ML), is currently at an early stage of adoption in low-income countries owing to a range of challenges, including data gathering, infrastructure limitations, and ethical considerations [12]. ML is used across many medical sectors such as diabetes management, cancer detection and treatment, cardiological assessments, mental health interventions, and radiological imaging analysis, demonstrating its broad applicability and transformative potential in healthcare [13], [14]. Significant progress has been achieved in radiology and pathology through AI's capability to provide digitally encoded images for computational analysis. Pathologists are aided by AI with image-based diagnostic options and improved interpretation of microscopic slides using electronic slides and computer-aided diagnostic tools [15], [16]. Recent advancements in ML algorithms have significantly impacted cardiological practices, particularly the stratification of patients at elevated risk of coronary plaque progression [17], [18].
AI shows impressive ability to identify skin lesions and has the potential to improve primary care in dermatology. However, further validation is necessary prior to its clinical application in dermatology [19]. AI is transforming ophthalmology by enhancing disease detection and prognosis in conditions such as diabetic retinopathy, macular degeneration, and retinopathy of prematurity, with deep learning precision. Nonetheless, its clinical integration as a supportive tool is being actively researched [20], [21]. In nephrology, AI enhances patient care by refining diagnostic and prognostic accuracy, optimizing dialysis outcomes, and improving monitoring of transplant recipients [22]. The application of ML in drug discovery has transformed the field by automating the complex process of molecular design and streamlining the synthesis of new drugs, leading to faster and more efficient therapeutic innovations [23].
AI’s role in healthcare extends beyond that of its individual specialties; it is used to optimize hospital operations [24]. Globally, AI’s impact on healthcare is extensive, with its applications offering solutions for improving the delivery of healthcare services [25], capable of transcribing clinical notes and organizing patient data into electronic health records. This indicates the potential for improved efficiency, accuracy, and patient care [26], [27]. AI systems also offer reliable secondary opinions to healthcare professionals, thereby significantly reducing their time burden [28]. The use of AI systems can also be advantageous for patients by providing personalized medication management, enhancing patient engagement, and potentially improving adherence to treatment plans, thereby leading to improved clinical outcomes and overall quality of life. Additionally, AI systems can support and empower patients in their self-management and decision-making processes, contributing to better health outcomes [29]. AI enables distant patient diagnoses and expands healthcare access to underserved rural areas. Although challenges persist, the future of AI in healthcare is promising [30]. Despite the significant potential of AI in the healthcare industry, its implementation in Somalia has been disrupted by various obstacles including inadequate infrastructure, scarcity of technical expertise, and limited access to high-quality data. Overcoming these challenges is essential for the successful integration of AI into healthcare systems in the region. Moreover, there are concerns regarding privacy and transparency in the use of patient data, which are exacerbated by the absence of strong regulatory frameworks and data protection laws. The technological and regulatory difficulties faced in implementing AI-based services could hinder their adoption and limit the benefits that AI could bring to healthcare systems in Somalia [31]. This study aimed to investigate the level of knowledge, attitudes, and practices of AI among healthcare professionals in Somalia as well as their familiarity with different AI technologies and practices.