Authors: Saurabh A Pahune
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Artificial intelligence (AI) has the potential to revo- lutionize healthcare delivery in rural areas by addressing various challenges such as scarcity of healthcare resources, lack of health- care professionals, and inadequate healthcare infrastructure. In this paper, we explore the role of AI in rural development in the healthcare domain, specifically focusing on how it can be leveraged to improve healthcare outcomes in rural areas. we outline the following main aspects of Artificial intelligence (AI) in rural development based on our findings from the literature review on Artificial Intelligence and various techniques used in the healthcare domain such as Robotics Process Automation (RPA), Machine Learning (ML), Natural Language Processing (NLP), Deep Learning(DL) including a recent breakthrough in AI technology. Identify the challenges and legal barriers in rural areas. Overall, this survey paper provides insights into the potential of AI to transform healthcare delivery in rural areas and highlights the need for a comprehensive and sustainable approach to leveraging AI for rural development in the healthcare domain. However, there are many challenges and limitations in their application. In this survey, we review recent Artificial Intelligence techniques that are used. We highlight the main challenges and limitations of current work and make recommendations for future research investigation. Furthermore, we consider the challenges and ethical concerns associated with AI deployment in rural healthcare settings, such as privacy and security risks, data quality and bias issues, and regulatory and legal barriers. By providing an overview of the current state of the art in AI and rural healthcare, this survey aims to inform and inspire further research and development in this important area.
The healthcare needs of rural communities are often ne- glected due to the lack of medical facilities, resources, and healthcare professionals. With the rapid advancements in Ar- tificial Intelligence (AI) technology, there is a growing interest in leveraging AI to address the healthcare challenges faced by rural areas. AI-based healthcare solutions have the potential to improve the accessibility, quality, and efficiency of healthcare delivery in rural communities. As a result healthcare industry is looking to implement in rural areas with new rising AI technologies. Artificial intelligence (AI) is a rapidly develop- ing field of computer science that uses computers to simu- late human learning, memory, analysis, and even innovation, which usually require human intelligence –. Artificial intelligence (AI) is a rapidly developing computer technology that has begun to be widely used in the medical field to improve the professional level and efficiency of clinical work, in addition to avoiding medical errors in rural areas .As per the rapid development of health information technology, electronic medical records (EMR), and personal health records (PHR), a huge amount of multimedia information in the format of documents, forms, images, and audio have been generated. Therefore, the application of artificial intelligence (AI) technology is expected to assist patients . AI-assisted clinical trials are capable of handling massive volumes of data and producing highly accurate . Medical AI companies develop systems that assist patients at every level. Patient’s medical data is also analyzed by clinical intelligence, which provides insights to assist them to improve their quality of life. Healthcare systems around the world face huge issues, including a lack of access, high costs, waste, and an older population. Pandemics like the coronavirus (COVID-19) put a strain on healthcare systems, resulting in a lack of pro- tective equipment, insufficient or erroneous diagnostic tests, overworked physicians, and a lack of information exchange.
In this short survey, we explore the various ways in which AI technology can contribute to the development of healthcare in rural areas. We examine the existing research on AI-based solutions for rural healthcare and identify the opportunities and challenges of using AI in this healthcare domain.
Also, we survey the current status of AI in healthcare as well as discuss its future with the usages of the dataset and various AI techniques being used. We first briefly review key relevant aspects that can contribute to the development of healthcare in rural areas.
a. Diagnosis and Treatment: AI-powered diagnostic tools can help healthcare providers in rural areas to accu- rately diagnose various diseases, including infectious diseases, chronic conditions, mental health disorders, clinical disease diagnosis , AI-enabled clinical decision-support systems may reduce diagnostic errors and augment intelligence to support decision-making . For instance, AI algorithms can analyze medical images such as X-rays, CT scans, and MRI scans, and provide automated diagnostic reports to healthcare providers –. Similarly, AI-powered treatment planning tools can assist healthcare providers in developing person- alized treatment plans for patients based on their medical history, symptoms, and other relevant factors , . For rural patients, virtual care can be a lifesaver since traveling to and from a doctor’s office or hospital can present a major challenge . Artificial intelligence (AI) algorithms have been employed to perform analysis of medical images and correlate symptoms and biomarkers from clinical data to characterize an illness and its prognosis .
b. Remote Patient Monitoring: AI-powered patient monitoring systems can help healthcare providers in rural areas to remotely monitor patients’ health status and detect early signs of deterioration. These systems can collect data from various sources such as wearable devices, electronic health records, and patient-reported data, and use AI algorithms to analyze the data and provide alerts to healthcare providers when necessary. . The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient monitoring (RPM) is one of the common healthcare applications that assist doctors to monitor patients with chronic or acute illness at remote locations, elderly people in-home care, and even hospitalized patients . Remote patient monitoring (RPM) is a rapidly growing field in the healthcare industry to assist patients in rural areas which tends to benefit to track of patient’s progress. Telemedicine for rural healthcare: AI-powered telemedicine services can help to improve healthcare access in rural areas by enabling patients to consult with healthcare providers remotely. Telemedicine services can be especially useful in areas where there is a shortage of healthcare professionals or inadequate healthcare infrastructure. For example, AI-powered chatbots can help patients to assess their symptoms and receive medical advice, while video conferencing tools can enable patients to consult with healthcare providers in real-time, Research in the medical industry has started to use AI’s strengths in data processing and analysis in telehealth . There are different areas of telemedicine and analyze the effect of AI in the field of health and medicine  and Telehealthcare is a broad term used to encompass the delivery of health-care services and information through ICT.
c. AI-powered health education tools(In rural areas): AI-powered health education tools can help rural patients learn about their health conditions and how to manage them. These tools make important information readily available by giving patients convenient access online or through mobile apps. And as generative AI tools become more prevalent, organizations will be able to use these systems to build their own patient education programs that appeal directly to their rural populations . AI-powered health education tools can help bridge the gap and provide valuable health information and resources to rural patients using various techniques be- ing used such as accessibility to health information, remote guidance, disease management and monitoring, Language and cultural considerations (AI-based Multi-linguistics technology  to assist rural areas with diverse populations and language barriers.).
d. AI-powered mobile health (mHealth) for rural areas: As per Author there are more than 97000 AI-enabled mobile healthcare applications(mHa) available on Google Play and Apple’s App which would be downloaded by 500 million people. This phenomenon has turned smartphones into medical kits for real-time health monitoring of patient’s activities, early predictability, disease screening, and improved medication adherence in patient monitoring . This technology has a few mandatory factors like internet connectivity, affordability of mobile devices, and digital literacy when implementing AI- powered Health solutions in rural areas. Ensuring that these solutions are user-friendly, culturally sensitive, and respect patient privacy and data security is crucial for their successful adoption and impact on rural healthcare .
e. AI-based rural disease surveillance and outbreak pre- diction: AI-based rural disease surveillance and outbreak prediction systems can play an important role in monitoring, detecting, and responding to disease outbreaks in rural areas .COVID-19-like pandemics, a mass surveillance system in terms of social distancing, mask-wearing, and body tem- perature detection was integrated into the system. Due to emerging threats to the safety of citizens and nations, many e-governments (e.g., China,USA, Australia, Germany, Russia, and so on) have begun tracking the movement and behavior of all residents by installing a number of mass surveillance systems points in all the towns, villages, streets, and public spaces to track and monitor suspects and detect suspicious patterns using various deep learning model.
f. Healthcare Decision-Making: AI-powered decision support tools can help healthcare providers in rural areas to make informed decisions about patient care. For instance, AI algorithms can analyze patient data and provide recommen- dations for diagnosis and treatment, as well as predict patient outcomes and identify potential risks , . AI-based sys- tems can offer decision-support tools that provide healthcare providers in rural areas with evidence-based recommendations for diagnosis, treatment options, and medication selection. These systems leverage vast amounts of medical literature, clinical guidelines, and patient data to assist providers in making informed decisions and reducing diagnostic errors.
In summary, AI can help to improve healthcare outcomes in rural areas by providing accurate diagnosis and treatment, improving healthcare access, facilitating patient monitoring, and supporting healthcare decision-making. However, the de- ployment of AI in rural healthcare settings also requires addressing several challenges such as privacy and security risks, data quality and bias issues, and regulatory and legal barriers.
Recently, healthcare in China’s rural areas has been benefiting from medical AI technology. According to a news report from South China Morning Post, a portable all-in- one diagnostic station (weighing 11 pounds), which can run 11 tests, including blood pressure, electrocardiographs, and routine urine and blood analyses, has been used in village healthcare settings. This device, which was developed by an internet healthcare company supported by the national rural healthcare program, can automatically upload results and medical records to an online data analysis system and generate a diagnosis for village health workers to review and reference. Several large-technology companies in China are also investing in AI-driven smart clinics for rural regions, such as AI-powered Chabot, which can communicate with patients, provide medical advice, and conduct online training for health workers in rural areas .
Due to the poor working environment, it is difficult to attract and retain high-quality healthcare providers in rural areas. To compensate for the shortage of physicians, many developing countries launch some abbreviated training pro- grams for becoming a physician, or they authorize nurses to perform certain physician tasks.
For example, there are many secondary medical vocational schools and junior medical colleges in China, in which students who graduated from middle or high school are given 3 years of medical training to become physicians. In 2014 in China, around 52% of physicians (2.9 million) had less than a bachelor’s degree, and most of them were working in rural areas of China. Although this can adequately meet the urgent demands for health workers in rural areas, the medical knowledge and skills of these doctors are insufficient .
II. INFORMATION SOURCES
Literature was retrieved from the following bibliographic databases for identifying research articles on Artificial In- telligence technology in healthcare rural development. These are IEEE, ScienceDirect, Springer, PubMed, Xplore, Google Scholar, Multidisciplinary Digital Publishing Institute (MDPI), arXiv to find more relevant articles. Each database was filtered to search the keywords and their combinations in the title, abstract, and keywords these databases provide a good assort- ment of peer-reviewed articles in the fields of Natural Lan- guage Processing(NLP), Artificial Intelligence(AI), Robotics Process Automation (RPA), Machine Learning (ML), Deep Learning (DL), Chatbot in healthcare.
A. Search strategy
The objective of this review is to identify journal articles, review articles, and conference papers related to the role of AI to assist in healthcare in rural areas. In this review, the paper address the following below research questions:
B. Dataset for Developing and Evaluating AI-based Rural Health Information
There are several datasets available that could potentially be used for developing and evaluating AI-based rural health information systems. Here are a few examples:
It’s important to note that accessing and using these datasets may require obtaining appropriate permissions and complying with relevant data privacy and security regulations. As the healthcare industry emerges into a new era of digital health driven by cloud data storage, distributed computing, and machine learning, healthcare data have become a premium commodity with value for private and public entities. Current frameworks of health data collection and distribution, whether from industry, academia, or government institutions, are imper- fect and do not allow researchers to leverage the full potential of downstream analytical efforts .
III. LITERATURE REVIEW ANALYSIS
In this section, we outline the following main aspects of AI in rural development based on our finding from the literature review: Artificial Intelligence various techniques used in the healthcare domain such Robotics Process Automation (RPA), Machine Learning (ML), Natural Language Processing (NLP), Deep Learning(DL).
A. Artificial Intelligence-based Robotics Process Automation in rural areas
B. Artificial Intelligence-powered decision support tools can help healthcare providers in rural areas
C. Artificial Intelligence-based disease diagnosis and treat- ment
D. Artificial Intelligence algorithms can analyze patient data and provide recommendations for diagnosis and treatment
IV. CHALLENGES AND ETHICAL CONCERNS ASSOCIATED WITH AI DEPLOYMENT IN RURAL HEALTHCARE
We would like to express our gratitude to all the researchers, healthcare professionals, and stakeholders who have con- tributed to the development of AI-powered healthcare systems in rural areas. Their work has been instrumental in shaping our understanding of the potential benefits and challenges associated with AI deployment in rural healthcare settings.
In conclusion, AI has the potential to transform healthcare delivery in rural areas, addressing various challenges such as the scarcity of healthcare resources, lack of healthcare professionals, and inadequate healthcare infrastructure. The deployment of AI-powered healthcare systems in rural areas can improve healthcare access, provide accurate diagnosis and treatment, and support healthcare decision-making. AI- powered telemedicine services, diagnostic tools, decision sup- port systems, and patient monitoring systems can enable remote healthcare delivery, reducing the need for patients to travel to healthcare facilities. However, the deployment of AI in rural healthcare settings also raises various challenges and ethical concerns, including privacy and security risks, data quality and bias issues, regulatory and legal barriers, limited access to technology, ethical concerns around autonomy, lack of human interaction, and cost and resource constraints.
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