CHUV
Exploring Artificial Intelligence to Predict Complications after Major Digestive Surgery
Major digestive surgery is associated with a high comorbidity (i.e. high risk of complications after surgery). Anticipating Postoperative complications (POC) may help and guide clinicians in the postoperative management of surgical patients. Unfortunately, the available tools in clinical practice are of restraint value due to their limited accuracy. Recently, artificial…
Machine-Learning Prognostication in Patients Undergoing Surgery for Hepatocellular Carcinoma (Liver Cancer)
Liver cancer is the second deadliest malignancy. It essentially accounts hepatocellular carcinoma (HCC). Surgery with liver resection is the main curative option but unfortunately, it is only recommended in patients with early HCC. Prognosis of HCC is particularly challenging and results from numerous attempts using various strategies remain relatively poor.Artificial…
Using Artifical Intelligence to Explore the Prognostic Value of Macroscopy in Liver Cancer
Liver cancer ranks third in terms of cancer-related mortality. Hepatocellular carcinoma (HCC) accounts for 90% of primary liver cancers. Tremendous efforts have been pursued to establish HCC prognostic, including clinical, radiological, pathological and even molecular readouts. Regardless of the strategy, the performance of these tools remains modest. Recent data using…
RuralUS: Ultrasound adapted to resource limited settings
Point-of-Care Ultrasound (PoCUS) is a powerfully versatile and virtually consumable-free clinical tool for the diagnosis and management of a range of diseases. While the promise of this tool in resource-limited settings may seem obvious, it’s implementation is limited by inter-user bias, requiring specific training and standardisation.This makes PoCUS a good…
Data Protection in Personalized Health
P4 (Predictive, Preventive, Personalized and Participatory) medicine is called to revolutionize healthcare by providing better diagnoses and targeted preventive and therapeutic measures. In order to enable effective P4 medicine, DPPH defines an optimal balance between usability, scalability and data protection, and develops required computing tools. The target result of the…
MedCo: Collective Protection of Medical Data
MedCo, developed in the LDS lab of professor Jean-Pierre Hubaux in collaboration with professor Bryan Ford’s DEDIS lab and the Lausanne University Hospital (CHUV), is the first operational system that makes sensitive medical-data available for research in a simple, privacy-conscious and secure way. It enables hundreds of clinical sites to…