Official opening

Opening keynote

A Sustainable Future for Learning AI in Healthcare - by Dimitrios Kalogeropoulos, Chief Executive, Global Health & Digital Innovation Foundation

Learning applications of AI have the power to utilize data to identify effective treatments, accelerate innovation and support decisions in clinical settings. Accelerating translational biomedical research and knowledge discovery is the most economically and socially valuable of all the uses of the AI tools available. Meaningful uses include early disease pathway detection, precision treatment, and the acquisition and analysis of early biomarkers and other telehealth data for primordial prevention, improved quality and patient-centric outcomes. Significant challenges are in the way of this future. We propose an elevated but meaningful role for AI that extends current practice in knowledge discovery with data recycling. An ecosystem model that reciprocally supports AI deployments in healthcare by enabling digital cooperation and connected AI applications for circular economies and biomedical discovery critical to viable and robust machine-learning paradigms.

Healthcare Business Transformation

How may AI help you? - Healthcare - by Ligia Kornowska, Leader, AI in Health Coalition

How AI is changing healthcare in Poland and CEE region? How can we implement AI solutions in health entities successfully? What are the obstacles? What will the future of healthcare look like?

Hospital Network Advisory: Listen to your meta data! - by Josema Cavanillas, Global Head of HCI Technology Consulting, Atos

Coffee Break

Healthcare Business Transformation

AI and Blockchain Framework for Healthcare Applications - By Muthu Ramachandran Research Consultant and Visiting Professor, AI Tech and Forti5 Tech

Blockchain applications in healthcare have grown rapidly and it includes record keeping, clinical trials, medical supply chains, patient monitoring, etc. where Blockchain characteristics are needed to improve safety, privacy, and security. AI and blockchain are among the most disruptive technologies and the integration of these two technologies will fundamentally reshape how we live, work, and interact. However, Porru, et. al (2017) have reported it lacks processes, tools, and techniques. Therefore, this paper provides a systematic framework for a secure and sustainable software engineering framework for healthcare blockchain applications. Secure and Sustainable Software Engineering Framework for Healthcare Blockchain Applications (S3EF-HBCA) significant contribution includes requirements engineering for healthcare, business process modelling for healthcare, domain modelling for healthcare, a reference architecture for healthcare, and validation by case study on Electronic Healthcare Record Management System (EHR), and simulation with Business Process Modelling Notation (BPMN) tools. The simulation shows it has taken 10.45 minutes to process 100 instances of real-time data and service requests. The overall result shows encouragement in terms of process, tools, standards, and testing.

Building a Safety Net for Healthcare: Enhancing Medical Mask Compliance with AI - by Jovan Bubonja, Applied Scientist, TomTom

Join us in exploring the future of healthcare safety with our AI-powered system. Our presentation showcases the transformative potential of Computer Vision in safeguarding public health, harnessing the data generated during the COVID-19 pandemic. Discover how our new benchmark dataset enables full utilization of DNN-based object detectors, addressing the critical issue of proper mask usage through a sophisticated blend of object detection, facial landmark detection, and clever heuristics. We look forward to seeing you and invite you to experience the capabilities of AI firsthand through our live demo.

Panel discussion

Future Trends in AI-Enhanced Healthcare: Insights from Industry and Academic Thought Leaders.

Mohamed Ramzi, Ognjen Milicevic, Nevena Veljkovic, Nebojsa Sabovic

Lunch Break

Gene Research with AI

Machine Learning Techniques for Omics Data Analysis - by Vesna Pajic, Bioinformatics Scientist, Velsera

In the last 15 years and more, Next Generation Sequencing technology has being developed constantly to become a powerful tool for getting insight into different biological processes within cells, tissues and organisms. The data coming from NGS have all properties of big data. In this talk, I will cover basic ML techniques used for their processing.

Do Androids Dream of Human Doctors? - by Ognjen Milicevic, Ml Tech Lead, HTEC

TBA - by Branka Zukic

Coffee Break

Mining & Managing Medical Data

Network neuroscience: where the brain and social networks works the same - by Ilya Zakharov, Senior researcher, Brainify.AI

Brain is the interconnected hub of billions of neurons. Apparently, these billions of neurons communicate with each other somewhat in the same way as billions of people. Network neuroscience, a cutting-edge field, is dedicated to understanding these fascinating parallels. This talk will shine a spotlight on the latest discoveries and insights from this exciting domain.

TBA - by Healthly

Keynote

TBA - by Anja Baresic, Rudjer Boskovic Institute

Drug and Clinical Research Analytics

Navigating the Kinetics & Dynamics of Drugs Through Data Insights for Informed Therapeutic Strategies - by Katarina Vucicevic, Full Professor of Pharmacokinetics, University of Belgrade - Faculty of Pharmacy

Understanding how drugs interact with biological systems is paramount for informed and effective therapeutic strategies. The focus of the presentation is the integration of data-driven approaches in deciphering the complexities of drug behavior within the human body. The talk will highlight the power of advanced statistical methods and data visualization in extracting meaningful insights from pharmacokinetic and pharmacodynamic data. By examining patient-specific factors and tailoring interventions based on the individual responses, the optimization of treatment outcomes and minimization of adverse effects is achieved. Real-world data and developed models will be showcased to exemplify the application of the methodology.

Improved Classification and Interpretation of EEG Data Using 3D SNN for STDP Learning and ESN as an On-Line Learning Classifier - by Dimitar Penkov

Novel hierarchical recurrent neural network architecture for on-line classification and interpretation of EEG data. It incorporates two dynamic pools of neurons - one based on NeuCube three dimensional structure of spiking neurons, spatially mapping a brain template and connected via spike-timing dependent plastic synapses and another Echo state neural network reservoir of sparsely connected hyperbolic tangent neurons that is able to learn on-line to classify continuously extracted from the Cube spike-rate features. The aim of the work was to interpret and classify in a brain-inspired manner dynamic spatio-temporal brain signals.

Coffee Break

Drug and Clinical Research Analytics

TBA - by Milos Todorovic, Founder, Ovio Care

TBA - by Uros Vilmanovic, Director, Clinical data Operations

Keynote

TBA - by Vladimir Brusic, Professor in Computer Science, University of Nottingham Ningbo China

Lunch Break

AI in Diagnostics & Medical Imaging

TBA - by Tomislav Krizan, CEO, Attomic Intelligence

Use-case: Using a data-driven approach in treating a serious medical condition - by Goran Dumic, Principal consultant, Syntio

We might never truly understand the power of data until seeing it save a life. This is a story about the importance of personalization in medical science and two parents fighting their child's epilepsy using data analytics when all standard protocols failed.

Coffee Break

AI in Diagnostics & Medical Imaging

Computer Vision in Melanoma Detection - by Djordje Hirs, Data Science Manager, Yettel

Application of AI in early melanoma detection