There is an ongoing debate on balancing the benefits and risks of artificial intelligence (AI) as AI is becoming critical to improving healthcare delivery and patient outcomes. Such improvements are essential in resource-constrained settings where millions lack access to adequate healthcare services, such as in Africa. AI in such a context can potentially improve the effectiveness, efficiency, and accessibility of healthcare services. Nevertheless, the development and use of AI-driven healthcare systems raise numerous ethical, legal, and socio-economic issues. Justice is a major concern in AI that has implications for amplifying social inequities. This paper discusses these implications and related justice concepts such as solidarity, Common Good, sustainability, AI bias, and fairness. For Africa to effectively benefit from AI, these principles should align with the local context while balancing the risks. Compared to mainstream ethical debates on justice, this perspective offers context-specific considerations for equitable healthcare AI development in Africa.

This work presents a survey of existing literature on the fusion of the Internet of Things (IoT) with robotics and explores the integration of these technologies for the development of the Internet of Robotics Things (IoRT). The survey focuses on the applications of IoRT in healthcare and agriculture, while also addressing key concerns regarding the adoption of IoT and robotics. Additionally, an online survey was conducted to examine how companies utilize IoT technology in their organizations. The findings highlight the benefits of IoT in improving customer experience, reducing costs, and accelerating product development. However, concerns regarding unauthorized access, data breaches, and privacy need to be addressed for successful IoT deployment.

From 2022 to 2030, the X-ray imaging systems segment is projected to maintain its lead in the Medical Digital Imaging System market, as per the recent analysis. The segment emerged as the dominant method in 2021, with the increasing prevalence of cardiovascular, respiratory, and gastrointestinal disorders driving the demand for X-ray imaging systems. Furthermore, the rising demand for minimally invasive procedures supports the market's growth. Technological advancements, such as portable and wireless X-ray devices, are expected to expand the segment further. SkyQuest's research suggests that the Asia Pacific region is also a major player in the Medical Digital Imaging System market.

The healthcare industry is facing increasing demand due to population growth, aging, and the rise of chronic diseases. According to the World Health Organization, the global demand for healthcare services is expected to increase by 15% by 2030. The healthcare industry is also one of the largest and fastest-growing sectors of the global economy, with spending expected to reach $10 trillion by 2022. To meet this demand and improve patient outcomes, healthcare providers are turning to technology. Telemedicine refers to the use of telecommunications and digital technologies to remotely diagnose and treat patients.

Over the years, the popularity and usage of wearable Internet of Things (IoT) devices in several healthcare services are increased. Among the services that benefit from the usage of such devices is predictive analysis, which can improve early diagnosis in e-health. However, due to the limitations of wearable IoT devices, challenges in data privacy, service integrity, and network structure adaptability arose. To address these concerns, we propose a platform using federated learning and private blockchain technology within a fog-IoT network. These technologies have privacy-preserving features securing data within the network. We utilized the fog-IoT network's distributive structure to create an adaptive network for wearable IoT devices. We designed a testbed to examine the proposed platform's ability to preserve the integrity of a classifier. According to experimental results, the introduced implementation can effectively preserve a patient's privacy and a predictive service's integrity. We further investigated the contributions of other technologies to the security and adaptability of the IoT network. Overall, we proved the feasibility of our platform in addressing significant security and privacy challenges of wearable IoT devices in predictive healthcare through analysis, simulation, and experimentation.

The knowledge report is published by STPI (Software Technology Parks of India), Ministry of Electronics & Information Technology in October, 2022 and has been prepared based on the guidance of STPIs CoEs like Neuron (Mohali), Image (Hyderabad), MedTech (Lucknow), and AIC STPI (Bengaluru) which focuses on delivering healthcare services through AI. The report is the result of in-depth market research and consultation conducted by Praxian Global Private Ltd who has been supported by the STPI. The report highlights the industry trends, enablers & inhibitors, policy & regulatory status and through these create a better understanding of the AI applications in healthcare and thereby encourage AI innovations. AI in healthcare in India can be a game-changer in multiple ways. It can make healthcare services affordable and available at remotest areas and bring in more efficiency in areas where it already exists.

"Artificial Intelligence is no more in fiction stories now. Today in our daily life, we can observe AI performing different tasks." Even if it is a customer or business organization, machines are vigorously improving the intelligence of humans. The mobile app sector is growing day by day. After the covid hit the world, it has become the basic need of many companies.

We are facing a global healthcare crisis today as the healthcare cost is ever climbing, but with the aging population, government fiscal revenue is ever dropping. To create a more efficient and effective healthcare system, three technical challenges immediately present themselves: healthcare access, healthcare equity, and healthcare efficiency. An autonomous mobile clinic solves the healthcare access problem by bringing healthcare services to the patient by the order of the patient's fingertips. Nevertheless, to enable a universal autonomous mobile clinic network, a three-stage technical roadmap needs to be achieved: In stage one, we focus on solving the inequity challenge in the existing healthcare system by combining autonomous mobility and telemedicine. In stage two, we develop an AI doctor for primary care, which we foster from infancy to adulthood with clean healthcare data. With the AI doctor, we can solve the inefficiency problem. In stage three, after we have proven that the autonomous mobile clinic network can truly solve the target clinical use cases, we shall open up the platform for all medical verticals, thus enabling universal healthcare through this whole new system.

Medical and health care facilities have improved since the emergence and incorporation of machine learning technologies. The application of machine learning in healthcare facilities has always increased the possibilities of patient satisfaction and the best healthcare treatment. Let us discuss the five best use cases that machine learning-based healthcare software development can offer the patient with the best outcomes in terms of treatment and facilities rendered at healthcare facilities. It is one of the best contributions that machine learning has made to the healthcare sector and changing the way patients get treated. The clinical decision support tool helps in analyzing huge data volume to recognize the kind of disease and to decide that treatment stage.

Artificial intelligence is emerging as a transformative technology that has demonstrated the potential to play a major role in many business verticals, from product design to banking and from cyber security to healthcare. Artificial intelligence offers endless possibilities to any business and its innovative nature will continue to influence the technology domain. One of the biggest AI revolutions has been witnessed in the healthcare sector, where it can impact both healthcare providers and patients. Artificial intelligence offers countless advantages in exploring the landscape of healthcare services, as it promises to incorporate innovation and technology into the healthcare system to deliver unique services to consumers. Artificial intelligence increases the efficiency of disease diagnosis, vaccine development, information integration, reduces administrative burdens and helps healthcare professionals make better data-driven decisions.