..
/ cscw / home /
 

Nazmun Ontika, M.Sc.

Nazmun Ontika

Mail: Nazmun.Ontika(at)uni-siegen.de

Raum: US-D 106

Telefon:

Vita

Nazmun Nisat Ontika is a research associate at the University of Siegen within the group on CSCW and Social Media (Prof. Dr. Volkmar Pipek). From November 2021 she is working on project „PAIRADS“. She studied computer science and received her Master’s from the University of Bonn.

Publikationen

2024

  • Saßmannshausen, S. M., Ontika, N. N., Pinatti De Carvalho, A. F., Rouncefield, M. & Pipek, V. (2024)Amplifying Human Capabilities in Prostate Cancer Diagnosis: An Empirical Study of Current Practices and AI Potentials in Radiology

    Proceedings of the CHI Conference on Human Factors in Computing Systems. New York, NY, USA, Publisher: Association for Computing Machinery, Pages: 1–20 doi:10.1145/3613904.3642362
    [BibTeX] [Abstract] [Download PDF]

    This paper examines the potential of Human-Centered AI (HCAI) solutions to support radiologists in diagnosing prostate cancer. Prostate cancer is one of the most prevalent and increasing cancers among men. The scarcity of radiologists raises concerns about their ability to address the growing demand for prostate cancer diagnosis, leading to a significant surge in the workload of radiologists. Drawing on an HCAI approach, we sought to understand the current practices concerning radiologists’ work on detecting and diagnosing prostate cancer, as well as the challenges they face. The findings from our empirical studies point toward the potential that AI has to expedite informed decision-making and enhance accuracy, efficiency, and consistency. This is particularly beneficial for collaborative prostate cancer diagnosis processes. We discuss these results and introduce design recommendations and HCAI concepts for the domain of prostate cancer diagnosis, with the aim of amplifying the professional capabilities of radiologists.

    @inproceedings{sasmannshausen_amplifying_2024,
address = {New York, NY, USA},
series = {{CHI} '24},
title = {Amplifying {Human} {Capabilities} in {Prostate} {Cancer} {Diagnosis}: {An} {Empirical} {Study} of {Current} {Practices} and {AI} {Potentials} in {Radiology}},
isbn = {9798400703300},
shorttitle = {Amplifying {Human} {Capabilities} in {Prostate} {Cancer} {Diagnosis}},
url = {https://dl.acm.org/doi/10.1145/3613904.3642362},
doi = {10.1145/3613904.3642362},
abstract = {This paper examines the potential of Human-Centered AI (HCAI) solutions to support radiologists in diagnosing prostate cancer. Prostate cancer is one of the most prevalent and increasing cancers among men. The scarcity of radiologists raises concerns about their ability to address the growing demand for prostate cancer diagnosis, leading to a significant surge in the workload of radiologists. Drawing on an HCAI approach, we sought to understand the current practices concerning radiologists’ work on detecting and diagnosing prostate cancer, as well as the challenges they face. The findings from our empirical studies point toward the potential that AI has to expedite informed decision-making and enhance accuracy, efficiency, and consistency. This is particularly beneficial for collaborative prostate cancer diagnosis processes. We discuss these results and introduce design recommendations and HCAI concepts for the domain of prostate cancer diagnosis, with the aim of amplifying the professional capabilities of radiologists.},
urldate = {2024-05-16},
booktitle = {Proceedings of the {CHI} {Conference} on {Human} {Factors} in {Computing} {Systems}},
publisher = {Association for Computing Machinery},
author = {Saßmannshausen, Sheree May and Ontika, Nazmun Nisat and Pinatti De Carvalho, Aparecido Fabiano and Rouncefield, Mark and Pipek, Volkmar},
month = may,
year = {2024},
keywords = {contextual inquiry, human-centered AI, prostate cancer diagnosis, radiologists},
pages = {1--20},
}

2023

  • Ontika, N. N., Sassmannshausen, S. M., Pinatti De Carvalho, A. F. & Pipek, V. (2023)PAIRADS: Hybrid Interaction Between Humans and AI in Radiology

    IN HHAI 2023: Augmenting Human Intellect doi:10.3233/FAIA230108
    [BibTeX] [Download PDF] 

    @incollection{ontika_pairads_2023,
title = {{PAIRADS}: {Hybrid} {Interaction} {Between} {Humans} and {AI} in {Radiology}},
shorttitle = {{PAIRADS}},
url = {https://ebooks.iospress.nl/doi/10.3233/FAIA230108},
urldate = {2023-07-31},
booktitle = {{HHAI} 2023: {Augmenting} {Human} {Intellect}},
publisher = {IOS Press},
author = {Ontika, Nazmun Nisat and Sassmannshausen, Sheree May and Pinatti De Carvalho, Aparecido Fabiano and Pipek, Volkmar},
year = {2023},
doi = {10.3233/FAIA230108},
keywords = {pairads},
pages = {395--397},
}

  • Ontika, N. N., Saßmannshausen, S. M., Pinatti De Carvalho, A. F. & Pipek, V. (2023)PAIRADS: Hybrid Interaction Between Humans and AI in Radiology

    IN HHAI 2023: Augmenting Human Intellect doi:10.3233/FAIA230108
    [BibTeX] [Download PDF] 

    @incollection{ontika_pairads_2023-1,
title = {{PAIRADS}: {Hybrid} {Interaction} {Between} {Humans} and {AI} in {Radiology}},
shorttitle = {{PAIRADS}},
url = {https://ebooks.iospress.nl/doi/10.3233/FAIA230108},
urldate = {2024-07-04},
booktitle = {{HHAI} 2023: {Augmenting} {Human} {Intellect}},
publisher = {IOS Press},
author = {Ontika, Nazmun Nisat and Saßmannshausen, Sheree May and Pinatti De Carvalho, Aparecido Fabiano and Pipek, Volkmar},
year = {2023},
doi = {10.3233/FAIA230108},
keywords = {italg},
pages = {395--397},
}

2022

  • Ontika, N. N., Saßmannshausen, S. M., Syed, H. A. & Pinatti De Carvalho, A. F. (2022)Exploring Human-Centered AI in Healthcare: A Workshop Report

    IN IRSI Report, Vol. 19, Pages: 1–54
    [BibTeX] [Abstract] [Download PDF]

    As a technique of improving the quality of life, AI has the potential to take a significant part in healthcare worldwide. However, in order to facilitate the widespread use of AI systems, we must first better comprehend the influence of AI on the healthcare sector. To create an acceptable intelligent system for healthcare, a comprehensive evaluation of ethically driven design, technology that effectively addresses human intellect, and human aspects of design is required. Our two-day workshop at the European Conference on CSCW in 2022 focused on Human-centered AI in the healthcare domain. In the workshop, we brought together researchers and practitioners in health informatics to accelerate conversations about developing usable and efficient intelligent systems that are more understandable and reliable for users.

    @article{ontika_exploring_2022-1,
series = {International reports on socio-informatics},
title = {Exploring {Human}-{Centered} {AI} in {Healthcare}: {A} {Workshop} {Report}},
volume = {19},
issn = {1861-4280},
url = {https://www.iisi.de/wp-content/uploads/2022/10/IRSI_V19I2.pdf},
abstract = {As a technique of improving the quality of life, AI has the potential to take a significant part in healthcare worldwide. However, in order to facilitate the widespread use of AI systems, we must first better comprehend the influence of AI on the healthcare sector. To create an acceptable intelligent system for healthcare, a comprehensive evaluation of ethically driven design, technology that effectively addresses human intellect, and human aspects of design is required. Our two-day workshop at the European Conference on CSCW in 2022 focused on Human-centered AI in the healthcare domain. In the workshop, we brought together researchers and practitioners in health informatics to accelerate conversations about developing usable and efficient intelligent systems that are more understandable and reliable for users.},
language = {English},
number = {2},
journal = {IRSI Report},
author = {Ontika, Nazmun Nisat and Saßmannshausen, Sheree May and Syed, Hussain Abid and Pinatti De Carvalho, Aparecido Fabiano},
editor = {Pipek, Volkmar and Rohde, Markus},
month = oct,
year = {2022},
keywords = {pairads},
pages = {1--54},
}

  • Ontika, N. N., Saßmannshausen, S. M., Syed, H. A., de Carvalho, A. F. P. & Pipek, V. (2022)‪Towards Human-Centered AI: Learning from Current Practices in Radiology‬

    [BibTeX] [Download PDF] 

    @inproceedings{ontika_towards_2022,
title = {‪{Towards} {Human}-{Centered} {AI}: {Learning} from {Current} {Practices} in {Radiology}‬},
shorttitle = {‪{Towards} {Human}-{Centered} {AI}},
url = {https://scholar.google.com/citations?view_op=view_citation&hl=de&user=3f5u4_kAAAAJ&citation_for_view=3f5u4_kAAAAJ:2osOgNQ5qMEC},
urldate = {2022-11-15},
author = {Ontika, Nazmun Nisat and Saßmannshausen, Sheree May and Syed, Hussain Abid and Carvalho, Aparecido Fabiano Pinatti de and Pipek, Volkmar},
year = {2022},
keywords = {pairads},
}

  • Ontika, N. N., Syed, H. A., Saßmannshausen, S. M., Harper, R. H., Chen, Y., Park, S. Y., Grisot, M., Chow, A., Blaumer, N., Pinatti de Carvalho, A. F. & Pipek, V. (2022)Exploring Human-Centered AI in Healthcare: Diagnosis, Explainability, and Trust

    doi:10.48340/ecscw2022_ws06
    [BibTeX] [Abstract] [Download PDF]

    AI has become an increasingly active area of research over the past few years in healthcare. Nevertheless, not all research advancements are applicable in the field as there are only a few AI solutions that are actually deployed in medical infrastructures or actively used by medical practitioners. This can be due to various reasons as the lack of a human-centered approach for the or non-incorporation of humans in the loop. In this workshop, we aim to address the questions relevant to human-centered AI solutions associated with healthcare by exploring different human-centered approaches for designing AI systems and using image-based datasets for medical diagnosis. We aim to bring together researchers and practitioners in AI, human-computer interaction, healthcare, etc., and expedite the discussions about making usable systems that will be more comprehensible and dependable. Findings from our workshop may serve as ‘terminus a quo’ to significantly improve AI solutions for medical diagnosis.

    @article{ontika_exploring_2022,
title = {Exploring {Human}-{Centered} {AI} in {Healthcare}: {Diagnosis}, {Explainability}, and {Trust}},
issn = {2510-2591},
shorttitle = {Exploring {Human}-{Centered} {AI} in {Healthcare}},
url = {https://dl.eusset.eu/handle/20.500.12015/4409},
doi = {10.48340/ecscw2022_ws06},
abstract = {AI has become an increasingly active area of research over the past few years in healthcare. Nevertheless, not all research advancements are applicable in the field as there are only a few AI solutions that are actually deployed in medical infrastructures or actively used by medical practitioners. This can be due to various reasons as the lack of a human-centered approach for the or non-incorporation of humans in the loop. In this workshop, we aim to address the questions relevant to human-centered AI solutions associated with healthcare by exploring different human-centered approaches for designing AI systems and using image-based datasets for medical diagnosis. We aim to bring together researchers and practitioners in AI, human-computer interaction, healthcare, etc., and expedite the discussions about making usable systems that will be more comprehensible and dependable. Findings from our workshop may serve as ‘terminus a quo’ to significantly improve AI solutions for medical diagnosis.},
language = {en},
urldate = {2022-06-27},
author = {Ontika, Nazmun Nisat and Syed, Hussain Abid and Saßmannshausen, Sheree May and Harper, Richard HR and Chen, Yunan and Park, Sun Young and Grisot, Miria and Chow, Astrid and Blaumer, Nils and Pinatti de Carvalho, Aparecido Fabiano and Pipek, Volkmar},
year = {2022},
note = {Accepted: 2022-06-22T04:34:51Z
Publisher: European Society for Socially Embedded Technologies (EUSSET)},
keywords = {pairads},
}

2020

  • Ontika, N. N., Kabir, M., Islam, A., Ahmed, E. & Huda, M. (2020)A Computational Approach to Author Identification from Bengali Song Lyrics

    doi:10.1007/978-981-13-7564-4_31
    [BibTeX] 

    @incollection{ontika_computational_2020,
title = {A {Computational} {Approach} to {Author} {Identification} from {Bengali} {Song} {Lyrics}},
isbn = {978-981-13-7563-7},
author = {Ontika, Nazmun Nisat and Kabir, Md and Islam, Ashraful and Ahmed, Eshtiak and Huda, Mohammad},
month = jan,
year = {2020},
doi = {10.1007/978-981-13-7564-4_31},
pages = {359--369},
}

2019

  • Ontika, N. N., Elezi, E. & Kacupaj, E. (2019)‪Dynamic Publications on the Blockchain‬

    Bonn, Germany
    [BibTeX] [Download PDF] 

    @inproceedings{ontika_dynamic_2019,
address = {Bonn, Germany},
title = {‪{Dynamic} {Publications} on the {Blockchain}‬},
url = {https://scholar.google.com/citations?view_op=view_citation&hl=de&user=3f5u4_kAAAAJ&citation_for_view=3f5u4_kAAAAJ:UeHWp8X0CEIC},
urldate = {2022-11-15},
author = {Ontika, Nazmun Nisat and Elezi, E and Kacupaj, E},
month = may,
year = {2019},
}

  • Ontika, N. N. (2019)Author Identification from Song Lyrics

    [BibTeX] 

    @mastersthesis{ontika_author_2019,
title = {Author {Identification} from {Song} {Lyrics}},
school = {United International University},
author = {Ontika, Nazmun Nisat},
year = {2019},
keywords = {Thesis},
}

2018

  • Ontika, N. N. (2018)‪Update? Install Now or Later! – A Synopsis of Update Behavior Research‬

    Bonn, Germany
    [BibTeX] [Download PDF] 

    @inproceedings{ontika_update_2018,
address = {Bonn, Germany},
title = {‪{Update}? {Install} {Now} or {Later}! - {A} {Synopsis} of {Update} {Behavior} {Research}‬},
shorttitle = {‪{Update}?},
url = {https://scholar.google.com/citations?view_op=view_citation&hl=de&user=3f5u4_kAAAAJ&citation_for_view=3f5u4_kAAAAJ:qjMakFHDy7sC},
urldate = {2022-11-15},
author = {Ontika, Nazmun Nisat},
month = may,
year = {2018},
}