8-10 September 2025 | Jesus College, University of Cambridge
AIiH 2025 will feature a plenary panel on Responsible AI for Healthcare, chaired by Prof. Elvira Perez Vallejos from University of Nottingham & UK RAI.
We are delighted to invite you to take part in the second International Conference on Artificial Intelligence in Healthcare (AIiH 2025), which will be held in the Jesus College, Cambridge from Monday 8 September to Wednesday 10 September 2025. The inaugural edition of the AIiH series was successfully held in the beautiful city of Swansea in September 2024 (click here to find out more).
AIiH aims to provide a prominent platform for researchers and practitioners who are devoted to improving healthcare using modern artificial intelligence. We recognise that healthcare applications present complex and sometimes unique challenges across a wide spectrum, from ethics to technical developments, that generic AI methods are often inadequate. By creating this dedicated forum, we encourage discussions and disseminations of efficient and effective AI solutions and technologies for healthcare, and in turn we hope to influence the research, technology adoption, and decision making in healthcare.
The conference welcomes submissions of novel research work in the following areas, but not limited to:
AIiH 2025 will continue working with Springer in publishing its conference proceedings. Accepted full-length papers of AIiH 2024 were published in two Springer LNCS volumes.
The conference also welcomes submission of short abstracts, which will be archived on zonodo.org (with DOIs) together with previously accepted short abstracts.
The winners of the Best Paper Award and the runner-up(s) will be invited to submit extended versions to the journal of Big Data Mining and Analytics (BDMA). BDMA has an impact factor of 7.7 and publishes state-of-the-art big data research and their applications, including healthcare.
This prestigious best paper award is to recognise the outstanding scientific quality of the work presented at the AIiH. The work must show outstanding scientific rigour, major novelty, and comprehensive comparative analysis. It is awarded based on Programme Chairs’ and reviewers’ recommendations. Presentation quality is also taken into consideration. The winners of AIiH 2024 can be found here, and the AIiH 2024 special issue is to be available in early 2025.
Furthermore, AIiH 2025 will invite a number of highly recommended papers to submit to a special issue in CAAI Artificial Intelligence Research (AIR). AIR publishes the state-of-the-art achievements in the field of artificial intelligence and its applications. The journal is Open Access with NO article processing fees.
Recent advancements in data generation and analytical technologies have accelerated the healthcare sector into a new era of personalised medicine. By integrating diverse datasets ranging from genomics and transcriptomics to proteomics, metabolomics, imaging, and clinical records using multi-modal and multi-omics approaches are transforming how we diagnose, treat, and prevent disease. Their promise is to facilitate personalised care, enabling clinicians to tailor interventions more precisely while also reducing healthcare costs. CLICK TITLE TO READ MORE
This Special Section aims to explore the transformative role of Artificial Intelligence (AI), intelligent systems, and assistive robotics in revolutionizing healthcare. It will focus on the design, development, and application of advanced technologies such as wearable devices, sensor networks, assistive robotics, haptics, and smart rehabilitation tools to enhance patient-centered care, disorder diagnosis, and movement understanding. CLICK TITLE TO READ MORE
AI is transforming healthcare with its great potential in combining and analyzing diverse data types, such as medical images, bio signals, and electronic health records, to enable comprehensive understanding of health conditions for improved decision-making. Generative models have demonstrated immense potential in diverse application areas, such as synthesizing new data for rare conditions and minority groups to improve the diversity of training data, improving model robustness and fairness while reducing reliance on scarce real-world examples. CLICK TITLE TO READ MORE
Long-term health conditions, such as cancer, diabetes, cardiovascular diseases, chronic respiratory conditions, and mental health disorders, pose significant challenges to healthcare systems worldwide. These conditions require continuous monitoring, personalized treatment plans, and proactive interventions to improve patient outcomes and reduce healthcare costs. AI has emerged as a transformative tool in addressing these challenges, offering innovative solutions for early diagnosis, predictive analytics, personalized medicine, and remote patient monitoring. CLICK TITLE TO READ MORE
Echocardiography is a cornerstone of cardiovascular diagnostics, providing crucial insights into cardiac structure and function. However, it remains highly dependent on operator skill and experience, leading to variability in image interpretation. The integration of AI into echocardiography holds transformative potential to standardise image acquisition, improve diagnostic accuracy, and enhance clinical workflows. This special session aims to bring together leading researchers, clinicians, and industry experts to explore the latest advancements and challenges in AI-powered echocardiography. CLICK TITLE TO READ MORE
This special session aims to explore the increasing role of AI in addressing the unique challenges of women’s healthcare including maternal health and wellbeing. A variety of social, physical, and emotional needs, along with specific medical factors and circumstances can influence women’s health. The advances in AI present a promising opportunity to revolutionise healthcare, offering new ways to improve services and enhance health outcomes for women. CLICK TITLE TO READ MORE
Time-series forecasting is a critical challenge in healthcare. Both on an individual level to anticipate patient outcomes and effectively manage disease, and on an institutional level to predict the dynamic demand on services. In recent years, time-series forecasting has improved significantly by integrating techniques from machine learning due to their ability to model complex, non-linear patterns in data, unlike traditional statistical methods. Additionally, the integration of increasingly large datasets from diverse sources, such as wearable devices and electronic health records and large repositories of secure data allows for more robust and personalised forecasts. CLICK TITLE TO READ MORE
This special session explores how Artificial Intelligence (AI) is revolutionising Autism Spectrum Disorder (ASD) diagnosis by addressing challenges such as delayed detection and reliance on subjective assessments. It highlights recent advances in AI-powered tools, including machine learning models for analysing multimodal data (e.g., speech, facial expressions, and neuroimaging), while addressing key considerations like interpretability, ethics, and equitable access. CLICK TITLE TO READ MORE
The oral and poster sessions of the conference will be taken place in the Jesus College and the conference banquet will be hosted in the Old Courts Hall of the Gonville & Caius College. These two colleges are among the oldest colleges in the University of Cambridge. Click on the link below to find our more.
Jesus College, University of Cambridge
Old Courts Hall, Gonville & Caius College, University of Cambridge
contact@aiih.cc