The development of intelligent software in recent years has grown rapidly. Mobile health has become a field of interest as a tool for childcare, especially as a means for parents of children with diverse diseases and a resource to promote their health conditions. Current systematic review was conducted to survey the functionalities of available applications on the mobile platform to support pediatrics intelligent diagnosis and children healthcare. Results which met the inclusion criteria (such as patient monitoring, decision support, diagnosis support) were obtained, assessed and organised into a checklist. In this study, 379 potential apps were identified using the search feature in Apple App Store and Google Play Store. After careful consideration of the selected apps, only three (Google Play Store) and one (iTunes Store), fulfilled all the general inclusion criteria and special criteria, such as intelligence tools. The results showed that Artificial Intelligence (AI) was used minimally in diagnostic apps due to a limited amount of mobile hardware and software, such as the reliable programming of intelligent algorithms.

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Top Mobile Applications in Pediatrics and Children's Health: Assessment and Intelligent Analysis Tools for a Systematic Investigation.

Artificial intelligence (AI) technologies enable Conversational Agents (CAs) to perform highly complex tasks in a human-like manner and may help people cope with anxiety to improve their mental health and well-being. To support patients with their mental well-being in an authentic way, CAs need to be imbued with human-like behavior, such as personality. In this paper we cover an innovative form of CA, so-called Personality-Adaptive Conversational Agents (PACAs) that automatically infer users’ personality traits and adapt accordingly to their personality. We empirically investigate their benefits and caveats in mental health care. The results of our study show that PACAs can be beneficial for mental health support, but they also raise concerns about trust and privacy issues. We present a set of relevant requirements for designing PACAs and provide solution approaches that can be followed when designing and implementing PACAs for mental health care.

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Requirements and Solution Approaches to Personality-Adaptive Conversational Agents in Mental Health Care


 The Doctor and the Algorithm combines insights from science and technology studies, critical algorithm studies, and public interest informatics to better understand how health artificial intelligence (AI) is made, promoted, regulated, and justified. It reviews the enthusiastic promises of health AI marketing communication and medical futurism as well as concerns about the dangerous and inequitable effects of AI that have been raised in critical algorithm studies and bioethics. In so doing, The Doctor and the Algorithm investigates promising new applications for health AI, as well as how these new technologies can replicate human biases under a veneer of objectivity and lead to considerable harms. The book also leverages AI, itself, to investigate the foundations of machine-learning technologies and the use of promotional language in health AI research. Along the way, it explores both how the overly enthusiastic embrace of health AI can lead to unintended consequences for patients and public health and how new initiatives in ethical and just AI can support better futures for algorithmic medicine. The Doctor and the Algorithm closes with recommendations for practices and frameworks that can support these more ethical and just approaches to health AI.

The Doctor and the Algorithm

Ethical Considerations on Artificial Intelligence in Dentistry: A Framework and Checklist.

Abstract This chapter investigates promotional claims about health artificial intelligence (AI) in press releases, popular media, and scientific publications. It details the inaccuracies of the “two-stage” model of scientific dissemination that posits an initial stage of dispassionate scientific inquiry followed by a subsequent stage of marketing and promotion. In so doing, the chapter analyzes how the same promotional claims are present in press releases, popular media, and scientific publications. To further explore hype in health AI, the chapter also reports on the development of twin AI systems that identify and classify promotional and hedged language in biomedical research. These systems support an analysis of the prevalence of promotional language in published research on health AI and the identification of those research reports at the greatest risk of exaggeration. 

HypeDx

The growing desire for better control of health outcomes and the increasing healthcare costs associated with disease treatment has led to a shift in the healthcare paradigm from reactive to proactive. Advances in artificial intelligence (AI), the study of intelligent machines that maximize their likelihood of achieving a goal, and the rise of mobile health technologies (e.g., wearable devices and smartphone applications) have enabled healthcare to take place outside of the traditional clinical setting. In this chapter, we detail how AI algorithms can improve wellness assessment, aid in personalizing intervention strategies to promote healthier lifestyle behaviors, and uncover previously unknown disease risk factors. Organized across three dimensions of wellness (physical, mental, and social), this chapter highlights studies that utilize AI to incorporate new data sources or reinterpret preexisting data sources to further advance preventative medicine.

Karnika Singh

Papers

Roles of artificial intelligence in wellness, healthy living, and healthy status sensing