Welcome to Future Medicine AI

Aims & scope of Future Medicine AI

We have reached a point where the pace of digital innovation is seemingly overwhelming. Digitization has begun to sculpt almost every area of society, transforming everything from judicial organizations to healthcare systems.

Change, at any pace, can be uncomfortable and undesirable. And although digital technology advancements pose challenges, they also present unique opportunities for empowerment and connection, particularly in the healthcare sector.

The potential growth of AI in medicine is not wholly reliant on the technology itself, but also how accepting the sector is to its implementation. At its core, much of medicine comes down to pattern recognition – health is quantifiable, and this is an area in which AI excels. Our health systems are suffering from increased pressure as a result of population growth, ageing populations and changing patient expectations, and AI offers an unprecedented opportunity to alleviate this strain and help reshape the practice of medicine.

AI has made it possible to improve health outcomes across the globe, through the creation of electronic health records, clinical decision support tools, wearable monitoring devices and data optimization techniques, to name a fraction of technologies that have enhanced the diagnosis and treatment of diseases and ailments [1].

Along with these benefits arise pertinent concerns and objections, regarding the adoption, integration and governance of AI technologies. Ethical issues are raised regarding privacy, safety, bias and trust. The successful deployment of AI tools in low-income and middle-income countries is a problem under continual deliberation. To achieve healthcare transformation across the globe, clinical AI must be directed by standards of trust, transparency and explainability, and these principles must be vigorously assessed and implemented, to protect end users from potential harm.

As AI reshapes medicine, Future Medicine AI will be positioned uniquely as a central hub for the communication and dissemination of the latest practice-changing research and high-quality industry insights, building a forward-thinking community of allied researchers, biomedical innovators and allied health practitioners, in a responsible and ethical way. It is essential to build digital healthcare technologies upon a foundation encompassing safety and responsibility, and as such, Future Medicine AI aims to cover these challenges and ethical issues to provide a critically reliable source of information for health regulators and policymakers. Future Medicine AI also welcomes the publication of policy digests, expert comments and original research to stimulate discussions around these critical challenges.

The topics covered cover nine core areas:

• Precision medicine;

• Medical imaging and biomedical diagnostics;

• Multi-omics research;

• Drug discovery and development;

• Next-generation clinical trials;

• Health management/optimization;

• Virtual reality;

• Ethics and regulation;

• Real world evidence.

In this issue

The papers in this inaugural issue represent the wide range of article types that can be published in the journal and the impact of that research in raising awareness for medical AI.

An Editorial by Manasi Soni (Kamdhenu University; Gandhinagar, India) explores the revolutionary effect of ChatGPT in reshaping healthcare [2]. The article discusses the use of such large language models in medical education, disease monitoring and patient guidance, however, it also cautions that these benefits should be maximized against risks to reliability, data privacy and evidence quality.

The featured Commentary by Kamala Maddali (Life Sciences Consulting; PA, USA) discusses some promising advances in therapeutic interventions for autism spectrum disorder, a group of complex neurodevelopmental conditions characterized by various symptoms affecting how people communicate and interact with the world [3]. The article focuses on virtual reality personalized therapies, which have shown potential in improving cognitive abilities and social skills among children suffering from autism spectrum disorder.

Danny Ruta (Guy's and St Thomas' NHS Foundation Trust; London, UK) et al. evaluate an AI-based oncology Clinical Decision Support System tool for its potential to assist and streamline the workloads of Multidisciplinary Teams [4]. The authors discovered that the Clinical Decision Support System can directly triage around 40% of breast cancer cases for faster decision-making, leading to shorter multidisciplinary meetings or more thorough analyses of complex cases.

A special report by Giovanni Briganti (Université de Liège; Belgium) describes the various powerful applications of large language models in healthcare [5]. As well as describing the core concepts of large language models, Giovanni Briganti addresses the ethical considerations and challenges that they pose to healthcare professionals, data scientists and AI experts.

The final article in this issue is a Perspective discussing the potential use of bioagents, including modified microbiota or toxins, carried by small drones (biote-bots) for hostile intentions [6]. Manousos Kambouris (University of Patras; Greece) et al. explore the unique challenges and ramifications of this concept, such as the technological adaptations for detection and countermeasures, while also considering regulatory and ethical issues.

Conclusion

Although much remains uncertain in this age of digital innovation, there is a global effort to increase awareness, understanding and integration of digital technologies within healthcare. In Future Medicine AI we hope to promote this knowledge by publishing peer-reviewed, open access research and opinion pieces exploring medical applications of AI.

The Editorial Board consists of a global panel of experts who bring a wealth of experience in medical AI and digital transformation. The journal provides a double-blind, peer-reviewed, fast-track publication option, rapid editorial communication and an in-house graphics team. We welcome your feedback and suggestions for future articles.

Lastly, I would like to take this opportunity to thank the editorial board members, contributing authors, peer reviewers and all the individuals involved in the publication of this issue. Particular thanks go to members of the Future Science Group team: Jade Parker (Senior Editor), Leela Ripton (Marketing Director), Awais Shahid (Senior Digital Marketing Executive), Ayomide Tayo-Oni (Digital Marketing Executive), Peter Lynch (IT Specialist), Peter Olima (Head of IT & Operations) and Danny Al-Khafaji (General Manager), who have helped develop this journal from the ground up.