Hasso-Plattner-Institut
Prof. Dr. Erwin Böttinger
  
 

Ariane Morassi Sasso

Research Assistant, PhD Candidate

Phone: + 49- (0) 331 5509-4827


Room: G-2.2 30


Email: ariane.morassi-sasso(at)hpi.de


Web: Linkedin, Research Gate, GitHub, Twitter

Research Topics

  • Representation and Integration of Health-Related Data
  • Machine Learning Applied to Healthcare
  • Information Retrieval
  • Digital Biomarkers

Master Thesis and Master Project Supervisions

Master Thesis

Felix Musmman (2020)

A WEB PLATFORM FOR ANALYZING MULTIMODAL SENSOR DATA IN THE CONTEXT OF DIGITAL HEALTH
(a web platform for analyzing multimodal sensor data in the context of digital health)

https://github.com/hpi-dhc/alps

Paper Published at ICHI 2020

 

Hendrik Folkerts (2020 - Ongoing)

Project: Transferring Knowledge on Blood Pressure Prediction using Photoplethysmograms: From the ICU to Daily Life

 

Master Projects

Wearables for monitoring and driving lifestyle changes (2019)

Students: Hendrik Folkerts, Arne Herdick, Corina Jaschek, Pit Wegner

Supervisors: Ariane Sasso, Suparno Datta, Lin Zhou, Justin Albert and Jonas Chromik

Project Proposal: Link

HPI only internal video: Link

 

Using Machine Learning Algorithms to predict Hypertension based on Electronic Health Records (2019/2020)

Students: Nina Kiwit, Jonas Cremerius, Margaux Gatrio, Melanie Hackl (Students)

Supervisors: Suparno Datta, Ariane Sasso, Dr. Girish Nadkarni, Prof. Dr. Erwin Böttinger (supervisors)

Project Proposal: Link

Video: Link

Conferences, Events and Reviews

Presenter

 

Panelist

Bachelor, Master ... and then PhD? Academic work in computer science

 

Reviewer

  • AMIA Symposium 2020
  • GHC 2020

Pre-Prints

HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population

Link

Accepted in: AIME (2020)

Publications

  • Sasso, A.M., Datta, S., Jeitler, M., Steckhan, N., Kessler, C.S., Michalsen, A., Arnrich, B., Boettinger, E.: HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population.International Conference on Artificial Intelligence in Medicine. p. 325--335. Springer (2020).
     
  • Morassi Sasso, A., Datta, S., Pfitzner, B., Zhou, L., Steckhan, N., Boettinger, E., Arnrich, B.: Unobtrusive Measurement of Blood Pressure During Lifestyle Interventions.Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare - Demos and Posters. EAI, Trento (2019).
     
  • Morassi Sasso, A., Datta, S., Pfitzner, B., Zhou, L., Steckhan, N., Boettinger, E., Arnrich, B.: Unobtrusive Measurement of Blood Pressure During Lifestyle Interventions.Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare - Demos and Posters. EAI, Trento (2019).
     
  • Oleynik, M., Faessler, E., Sasso, A.M., Kappattanavar, A., Bergner, B., da Cruz, H.F., Sachs, J.-P., Datta, S., Boettinger, E.: HPI-DHC at TREC 2018 Precision Medicine Track.Notebook papers of the TREC 2018 conference. pp. 1-9 (2018).
     
  • Yoshiura, V.T., Azevedo-Marques, J.~ao M., Rzewuska, M., Vinci, A.L.T., Sasso, A.M., Miyoshi, N.S.B.~ao, Furegato, A.R.F., Rijo, R.P.C.L., Del-Ben, C.M., Alves, D.: A web-based information system for a regional public mental healthcare service network in Brazil.International journal of mental health systems.11,1 (2017).
     
  • Patr~ao, D.F.C., Oleynik, M., Massicano, F., Sasso, A.M.: Recruit-An Ontology Based Information Retrieval System for Clinical Trials Recruitment.MedInfo. p. 534--538 (2015).
     
  • Massicano, F., Sasso, A., Tomaz, H., Oleynik, M., Nobrega, C., Patrao, D.F.C.: An Ontology for TNM Clinical Stage Inference.ONTOBRAS (2015).