Why digital medicine depends on interoperability

Digital data are anticipated to transform medicine. However, most of today's medical data lack interoperability: hidden in isolated databases, incompatible systems and proprietary software, the data are difficult to exchange, analyze, and interpret. This slows down medical progress, as technologies that rely on these data - artificial intelligence, big data or mobile applications - cannot be used to their full potential. In this article, we argue that interoperability is a prerequisite for the digital innovations envisioned for future medicine. We focus on four areas where interoperable data and IT systems are particularly important: (1) artificial intelligence and big data; (2) medical communication; (3) research; and (4) international cooperation. We discuss how interoperability can facilitate digital transformation in these areas to improve the health and well-being of patients worldwide

A comprehensive review of artificial intelligence for pharmacology research

With the innovation and advancement of artificial intelligence, more and moreartificial intelligence techniques are employed in drug research, biomedicalfrontier research, and clinical medicine practice, especially, in the field ofpharmacology research. Thus, this review focuses on the applications ofartificial intelligence in drug discovery, compound pharmacokinetic prediction,and clinical pharmacology. We briefly introduced the basic knowledge anddevelopment of artificial intelligence, presented a comprehensive review, and then summarized the latest studies and discussed the strengths and limitations of artificial intelligence models. Additionally, we highlighted several important studies and pointed out possible research directions

Thirty years of artificial intelligence in medicine (AIME) conferences: A review of research themes

Over the past 30 years, the international conference on Artificial Intelligence in MEdicine (AIME) has been organized at different venues across Europe every 2 years, establishing a forum for scientific exchange and creating an active research community. The Artificial Intelligence in Medicine journal has published theme issues with extended versions of selected AIME papers since 1998

Artificial Intelligence and Endo-Histo-OMICs: New Dimensions of Precision Endoscopy and Histology in Inflammatory Bowel Disease

Integrating artificial intelligence into inflammatory bowel disease (IBD) has the potential to revolutionise clinical practice and research. Artificial intelligence harnesses advanced algorithms to deliver accurate assessments of IBD endoscopy and histology, offering precise evaluations of disease activity, standardised scoring, and outcome prediction. Furthermore, artificial intelligence offers the potential for a holistic endo-histo-omics approach by interlacing and harmonising endoscopy, histology, and omics data towards precision medicine. The emerging applications of artificial intelligence could pave the way for personalised medicine in IBD, offering patient stratification for the most beneficial therapy with minimal risk. Although artificial intelligence holds promise, challenges remain, including data quality, standardisation, reproducibility, scarcity of randomised controlled trials, clinical implementation, ethical concerns, legal liability, and regulatory issues. The development of standardised guidelines and interdisciplinary collaboration, including policy makers and regulatory agencies, is crucial for addressing these challenges and advancing artificial intelligence in IBD clinical practice and trials

A review of applications of artificial intelligence in veterinary medicine

Artificial intelligence is a newer concept in veterinary medicine than human medicine, but its existing benefits illustrate the significant potential it may also have in this field. This article reviews the application of artificial intelligence to various fields of veterinary medicine. Successful integration of different artificial intelligence strategies can offer practical solutions to issues, such as time pressure, in practice. Several databases were searched to identify literature on the application of artificial intelligence in veterinary medicine. Exclusion and inclusion criteria were applied to obtain relevant papers. There was evidence for an acceleration of artificial intelligence research in recent years, particularly for diagnostics and imaging. Some of the benefits of using artificial intelligence included standardisation, increased efficiency, and a reduction in the need for expertise in particular fields. However, limitations identified in the literature included a requirement for ideal situations for artificial intelligence to achieve accuracy and other inherent, unresolved issues. Ethical considerations and a hesitancy to engage with artificial intelligence, by both the public and veterinarians, are further barriers that must be addressed for artificial intelligence to be fully integrated in daily practice. The rapid growth in artificial intelligence research substantiates its potential to improve veterinary practice

Artificial intelligence and thyroid disease management: considerations for thyroid function tests

Artificial intelligence (AI) is transforming healthcare and offers new tools in clinical research, personalized medicine, and medical diagnostics. Thyroid function tests represent an important asset for physicians in the diagnosis and monitoring of pathologies. Artificial intelligence tools can clearly assist physicians and specialists in laboratory medicine to optimize test prescription, tests interpretation, decision making, process optimization, and assay design. Our article is reviewing several of these aspects. As thyroid AI models rely on large data sets, which often requires distributed learning from multi-center contributions, this article also briefly discusses this issue

Editorial: On the “Human” in Human-Artificial Intelligence Interaction

ST was supported by MIUR-Italian Ministry of University and Research (Department of Excellence Italian Law n.232, 11th December 2016) for University of Milan. ID was supported by Fondazione Umberto Veronesi.Artificial Intelligence or technologies able to perform tasks normally requiring human cognitive processes (e.g., reasoning, perception) are revolutionizing many fields such as healthcare and business. For example, medical doctors use artificial intelligence to analyze pathological data and patients’ genomic profiles to identify personalized treatment according to a precision medicine approach. In general, artificial intelligence represents an invaluable resource for any professional dealing with the need to understand data and make decisions.Ministry of Education, Universities and Research (MIUR)Fondazione Umberto Verones