Maria Christoforaki

ORCID: 0000-0002-7047-1057
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About
Contact & Profiles
Research Areas
  • Automated Reconstruction of Fragmented Objects
  • Shape Matching and Object Recognition
  • Management and Reproducibility of Scientific Workflows
  • Neuroaesthetics and Aesthetic Perception in Neuroscience
  • Ethical Implications of Artificial Intelligence
  • 3D Geospatial Modelling Techniques
  • Semantic Web and Ontology Development
  • Artificial Intelligence in Medicine
  • Temporal, Spatial, and Social Aspects of Cultural Heritage Studies
  • Architectural Geometry and Artistic Representation
  • Society and Economy in Ancient Mediterranean Civilizations
  • Trajectory Data Mining and Analysis
  • Interdisciplinary Study of Fashion and Clothing
  • Archaeological Remote Sensing using Remote Sensing Techniques
  • Impact of Mental Illness on Family Caregivers
  • Cyberbiosecurity and Legal Implications of AI Technology
  • Impact of Big Data Analytics on Business Performance
  • Family-Centered Care in Intensive Care Units
  • Scientific Computing and Data Analysis with Python
  • Education, Culture, and Community Development
  • Adversarial Robustness in Deep Learning Models
  • Software Development and Engineering Processes
  • Artificial Intelligence in Service Industry
  • Image Feature Retrieval and Recognition Techniques
  • Language Discourse and Communication Studies

University Hospital Cologne
2022-2024

University of Cologne
2021-2024

University Hospital of Heraklion
2023

University of St. Gallen
2020

University of Passau
2016-2019

Foundation for Research and Technology Hellas
1996

The explosion of data-driven applications using Artificial Intelligence (AI) in recent years has given rise to a variety ethical issues regarding data collection, annotation, and processing mostly opaque algorithms, as well the interpretation employment results AI pipeline. ubiquity negatively impacts sensitive areas, ranging from discrimination against vulnerable populations privacy invasion environmental cost that these algorithms entail, puts into focus on ever present domain ethics. In...

10.3390/app12094130 article EN cc-by Applied Sciences 2022-04-20

The use of Artificial Intelligence (AI) applications in a growing number domains the latest years has put into focus Ethical Legal and Societal Aspects (ELSA) these technologies relevant challenges they pose.
 In this paper, we propose an ELSA Curriculum for Data Scientists aiming to raise awareness about their work, provide them with common language domain experts cooperate find appropriate solutions, finally, incorporate data science workflow not be seen as impediment or superfluous...

10.20944/preprints202401.0622.v1 preprint EN 2024-01-08

The use of artificial intelligence (AI) applications in a growing number domains recent years has put into focus the ethical, legal, and societal aspects (ELSA) these technologies relevant challenges they pose. In this paper, we propose an ELSA curriculum for data scientists aiming to raise awareness about their work, provide them with common language domain experts order cooperate find appropriate solutions, finally, incorporate science workflow. should not be seen as impediment or...

10.3390/ai5020025 article EN cc-by AI 2024-04-11

In Greece, patients undergoing hemodialysis (HD) usually go to dialysis centers two or three times a week for three/four hours per session because the treatment home is unavailable; therefore, caregivers should perform supportive transportation and care functions.This study was designed assess burden quality of life in peritoneal (PD) record their attitude toward Coronavirus Disease-2019 (COVID-19).We studied dialysis. A total 80 took part (30 PD 50 HD). The final form questionnaire based on...

10.1007/978-3-031-31986-0_27 article EN Advances in experimental medicine and biology 2023-01-01

In this paper, we report on our efforts for using Deep Learning classifying artifacts and their features in digital visuals as a part of the Neoclassica framework. It was conceived to provide scholars with new methods analyzing aesthetic forms from era Classicism. The framework accommodates both traditional knowledge representation formal ontology data-driven discovery, where cultural patterns will be identified by means algorithms statistical analysis machine learning. We created approach...

10.48550/arxiv.1710.04943 preprint EN cc-by arXiv (Cornell University) 2017-01-01

In the last years, image classification processes like neural networks in area of art-history and Heritage Informatics have experienced a broad distribution (Lang Ommer 2018). These methods face several challenges, including handling comparatively small amounts data as well high-dimensional Digital Humanities. Here, Convolutional Neural Network (CNN) is used that output not, usual, series flat text labels but semantically loaded vectors. vectors result from Distributional Semantic Model...

10.48550/arxiv.2001.02372 preprint DE cc-by arXiv (Cornell University) 2020-01-01
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