Digital Health

-> 5th floor, room ZLO5.01

Event sponsored by SAS (www.sas.com)

Important note: this event will take place in Zurich.

Talk #1

Title: From Spot Checks to Continuous Temperature Insights in Digital Health (Ali Ahari)

Abstract: Core body temperature (CBT) is a critical vital sign for detecting fever and monitoring patient health, yet traditional intermittent measurements provide only limited point accuracy and are often cumbersome to obtain. This talk introduces a non-invasive, continuous CBT monitoring solution based on heat-flux technology, which compensates for environmental influences and delivers medically accurate readings around the clock. We will discuss its integration into wearable devices, clinical validation studies, and how continuous monitoring reduces nursing workload, enables early detection of deterioration, and improves patient outcomes in hospital and remote care settings.

Bio: Ali Ahari is a data scientist at greenteg AG, where he works on data analytics and modeling for physiological monitoring solutions. His focus is on transforming sensor data into reliable insights for applications in digital health, sports, and research.

Talk #2

Title: AI for Phage Therapy: Enabling Precision Treatment Through Genomic Intelligence (Farzeneh Labbaf)

Abstract: Phage therapy—the use of bacteriophages to treat bacterial infections—offers a promising alternative to antibiotics, yet its adoption is limited by the complexity of matching the right phage to a patient’s bacterial strain. At PreciseHealth, we develop PhageMatch, a data-driven platform that empowers clinicians to analyze bacterial and phage genomes and use AI to identify effective therapeutic matches. The platform integrates machine learning with genomics and bioinformatics pipelines to automate analysis, improve accuracy, and accelerate clinical decision-making. This talk will present the technical backbone of PhageMatch—our data infrastructure, model development process, and workflow orchestration—and discuss the challenges of scaling AI for real-world phage therapy applications in clinical settings.

Bio: Farzeneh Labbaf is a Machine Learning Engineer at PreciseHealth, where she develops AI-driven platforms to advance phage therapy and make it more accessible to clinicians. She holds a Master’s degree in Computer Science, specializing in computational biology and data science. Farzeneh has worked on applying machine learning, deep learning, and multi-omics analysis to real-world biomedical problems, building scalable and production-ready AI systems. Her work spans model development, deployment, and workflow orchestration, with a focus on turning complex biological and clinical data into actionable insights.

Talk #3

Title: How computer vision can support precision oncology? (Olesia Kondrateva)

Abstract: Oncology increasingly relies on complex molecular profiling, yet for most patients the only available material is still the H&E-stained tissue slide. What clinically useful signals can we read from these images? I will briefly review key computer-vision approaches for histopathology and what they have been shown to predict.
I will then present a framework that highlights which tumor regions are most informative for predicting clinically relevant features. It combines CNNs pretrained on large-scale pathology datasets with graph-based representations of cell-cell and microenvironment interactions, integrating both visual patterns and spatial tissue organization.

Bio: I am a PhD student in Prof. Maria Anisimova’s lab in the joint ZHAW/UZH PhD program in Data Science. I develop interpretable deep-learning methods for histopathology to predict genomic and therapy-relevant features directly from tumor slides. I actively support open-source science, publishing cancer-research tools and reproducible workflows on GitHub. My work has been presented on different conferences, including SIB Days and REFRACT, where I received a poster award. Overall, my goal is to make better use of readily available slide data to lower diagnostic costs and provide clinicians with transparent, spatially grounded insights.

Talk #4

Title: Driving Innovation in Digital Health with SAS Viya (Tamara Fischer)

Abstract: Digital health is transforming the way we approach patient care, enabling data-driven insights for topics like precision diagnostics or personalized medicine. In this session, I will explore how SAS Viya empowers healthcare professionals and data scientists to develop advanced analytical solutions that improve outcomes and efficiency. I’ll demonstrate how to leverage modern Machine Learning methods and local model interpretability methods for AI-driven decision support. Join me to learn practical approaches for leveraging data and analytics to shape the future of digital health.