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Janusz Wojtusiak
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2020 – today
- 2024
- [c48]Atefehsadat Haghighathoseini, Mohammad Qodrati, Hua Min, Timothy Leslie, Cara Frankenfeld, Nirup M. Menon, Janusz Wojtusiak:
Selection Bias from Data Processing in N3C. ICHI 2024: 234-241 - 2023
- [c47]Hua Min, Hedyeh Mobahi
, Janusz Wojtusiak:
Application of Synthetic Datasets across Courses in Health Informatics Education. ICHI 2023: 677-681 - 2022
- [c46]Wejdan Bagais, Janusz Wojtusiak:
Dashboard for Machine Learning Models in Health Care. HEALTHINF 2022: 482-490 - [c45]Ying Wang, Patricia Tran, Janusz Wojtusiak:
From Wearable Device to OpenEMR: 5G Edge Centered Telemedicine and Decision Support System. HEALTHINF 2022: 491-498 - [c44]Janusz Wojtusiak, Negin Asadzadehzanjani:
Discussion on Comparing Machine Learning Models for Health Outcome Prediction. HEALTHINF 2022: 711-718 - [c43]Janusz Wojtusiak, Hua Min
From Undergraduate to Doctoral Health Informatics Training: A Data Focus. ICHI 2022: 575-584 - 2021
- [j12]Janusz Wojtusiak, Reyhaneh Mogharab Nia:
Location prediction using GPS trackers: Can machine learning help locate the missing people with dementia? Internet Things 13: 100035 (2021) - [j11]Janusz Wojtusiak
COVID-19 Symptom Monitoring and Social Distancing in a University Population. J. Heal. Informatics Res. 5(1): 114-131 (2021) - [j10]Janusz Wojtusiak
Computational Barthel Index: an automated tool for assessing and predicting activities of daily living among nursing home patients. BMC Medical Informatics Decis. Mak. 21(1): 17 (2021) - [c42]Wejdan Bagais, Janusz Wojtusiak:
Dashboard for Machine Learning Models in Health Care. AMIA 2021 - [c41]Ying Wang, Janusz Wojtusiak:
Active Learning Based User-Defined Chest X-Ray Diagnosis System Leveraging 5G Infrastructure for COVID-19 Variant Detection. AMIA 2021 - [c40]Janusz Wojtusiak, Wejdan Bagais, Hedyeh Mobahi, Elina Guralnik, Amira Roess, Farrokh Alemi:
Do Clusters and Sequence of Symptoms Predict COVID-19 Test Results? AMIA 2021 - [c39]Janusz Wojtusiak, Negin Asadzaehzanjani, Cari Levy, Farrokh Alemi, Allison E. Williams:
Online Decision Support Tool that Explains Temporal Prediction of Activities of Daily Living (ADL). HEALTHINF 2021: 629-636 - [c38]Janusz Wojtusiak:
Reproducibility, Transparency and Evaluation of Machine Learning in Health Applications. HEALTHINF 2021: 685-692 - [c37]Negin Asadzadehzanjani, Janusz Wojtusiak:
Administrative Health Data Representation for Mortality and High Utilization Prediction. Poly/DMAH@VLDB 2021: 133-150 - [c36]Janusz Wojtusiak, Ying Wang, Varalakshmi Vakkalagadda, Farrokh Alemi, Amira Roess
Using Wi-Fi Infrastructure to Predict Contacts During Pandemics. ICHI 2021: 347-356 - 2020
- [c35]Reyhaneh Mogharab Nia, Janusz Wojtusiak:
Using Landmark Information to Enhance Location Prediction for Missing People with Alzheimer's Disease. AMIA 2020 - [c34]Janusz Wojtusiak, Eunika Mercier-Laurent, Cindi Punihaole:
Introduction to the Minitrack on AI and Sustainability: The Use of AI in Sustainability Initiatives. HICSS 2020: 1-2
2010 – 2019
- 2019
- [c33]Negin Asadzadehzanjani, Janusz Wojtusiak, Allison E. Williams, Cari Levy:
Generic vs. Specialized Models for Assessing Disabilities among People with Dementia. AMIA 2019 - [c32]Hedyeh Mobahi, Hua Min, Janusz Wojtusiak:
Synthetic Data for Teaching Data Integration in Informatics Graduate Program. AMIA 2019 - [c31]Janusz Wojtusiak, Reyhaneh Mogharab Nia, U. Nalla B. Durai, Beverly Middle, Robert Koester, Catherine Tompkins:
Using GPS to Locate the Missing and Track Wandering in People with Alzheimer's Disease. AMIA 2019 - [c30]Amr ElRafey, Janusz Wojtusiak:
Rapidly Determining the Starting Sample Size in Progressive Sampling: Mean Convergence is Sufficient. ICDM 2019: 278-289 - 2018
- [c29]Mojtaba Zare, Janusz Wojtusiak:
Weighted Itemsets Error (WIE) Approach for Evaluating Generated Synthetic Patient Data. ICMLA 2018: 1017-1022 - 2017
- [j9]Hua Min
Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology. J. Biomed. Semant. 8(1): 39:1-39:8 (2017) - [c28]Janusz Wojtusiak, Eman Elashkar
C-Lace: Computational Model to Predict 30-Day Post-Hospitalization Mortality. HEALTHINF 2017: 169-177 - 2016
- [j8]Che Ngufor, Janusz Wojtusiak:
Extreme logistic regression. Adv. Data Anal. Classif. 10(1): 27-52 (2016) - [c27]Fatemah M. Aloudah, Janusz Wojtusiak:
Towards Automated Selection of Patient-Specific Education Materials in Ambulatory Care Settings. AMIA 2016 - [c26]Hua Min, Talha Oz, Sava Vukomanovic, Hedyeh Mobahi, Katherine Irvin, Ilirjeta Krasniqi, Janusz Wojtusiak:
Applying Machine Learning Methods to Predict Activities of Daily Living for Cancer Patients. AMIA 2016 - [c25]Hua Min, Talha Oz, Sava Vukomanovic, Hedyeh Mobahi, Katherine Irvin, Ilirjeta Krasniqi, Janusz Wojtusiak:
Visualizing the Effects of Cancers on Relationships Between Comorbidities and Activities of Daily Living. AMIA 2016 - [c24]Janusz Wojtusiak, Hua Min, Eman Elashkar
Guiding Supervised Learning by Bio-Ontologies in Medical Data Analysis. AI4KM@IJCAI 2016: 1-18 - 2015
- [c23]Che Ngufor, Janusz Wojtusiak, Jyotishman Pathak:
A Systematic Prediction of Adverse Drug Reactions Using Pre-clinical Drug Characteristics and Spontaneous Reports. ICHI 2015: 76-81 - 2014
- [c22]Janusz Wojtusiak, Che Ngufor, Lorens Helmchen, Jack Hadley:
Creating Clinically Homogeneous Groups of Prostate Cancer Patients. AMIA 2014 - [c21]Che Ngufor, Janusz Wojtusiak, Andrea Hooker, Talha Oz, Jack Hadley:
Extreme Logistic Regression: A Large Scale Learning Algorithm with Application to Prostate Cancer Mortality Prediction. FLAIRS 2014 - [p3]Janusz Wojtusiak:
Rule Learning in Healthcare and Health Services Research. Machine Learning in Healthcare Informatics 2014: 131-145 - 2013
- [j7]Che Ngufor, Janusz Wojtusiak:
Unsupervised Labeling of Data for Supervised Learning and its Application to Medical claims Prediction. Comput. Sci. 14(2): 191-214 (2013) - [c20]Andrej Kolacevski, Janusz Wojtusiak:
Machine Learning-based Detection of Health Data Elements. AMIA 2013 - [c19]Talha Oz, Che Ngufor, Janusz Wojtusiak:
Mining Progress Notes for Prediction of Activities of Daily Living. AMIA 2013 - 2012
- [j6]Janusz Wojtusiak, Tobias Warden, Otthein Herzog
Machine learning in agent-based stochastic simulation: Inferential theory and evaluation in transportation logistics. Comput. Math. Appl. 64(12): 3658-3665 (2012) - [j5]Ryszard S. Michalski, Janusz Wojtusiak:
Reasoning with unknown, not-applicable and irrelevant meta-values in concept learning and pattern discovery. J. Intell. Inf. Syst. 39(1): 141-166 (2012) - [j4]Janusz Wojtusiak, Tobias Warden, Otthein Herzog
The learnable evolution model in agent-based delivery optimization. Memetic Comput. 4(3): 165-181 (2012) - [c18]Katherine Irvin, Janusz Wojtusiak:
Comparison of Classification Learning Methods for Medical Claims Payments. AMIA 2012 - [c17]Janusz Wojtusiak:
Recent Advances in AQ21 Rule Learning System for Healthcare Data. AMIA 2012 - [c16]Hua Min
Clinical data analysis using ontology-guided rule learning. MIX-HS 2012: 17-22 - [c15]Janusz Wojtusiak:
Semantic Data Types in Machine Learning from Healthcare Data. ICMLA (1) 2012: 197-202 - 2011
- [c14]Janusz Wojtusiak, Tobias Warden, Otthein Herzog
Agent-based Pickup and Delivery Planning: The Learnable Evolution Model Approach. CISIS 2011: 1-8 - [c13]Janusz Wojtusiak, Katherine Irvin, Aybike Birerdinc, Ancha V. Baranova
Using Published Medical Results and Non-homogenous Data in Rule Learning. ICMLA (2) 2011: 84-89 - [c12]Janusz Wojtusiak, Che Ngufor, John Shiver, Ronald Ewald:
Rule-Based Prediction of Medical Claims' Payments: A Method and Initial Application to Medicaid Data. ICMLA (2) 2011: 162-167 - [p2]Janusz Wojtusiak, Ancha V. Baranova
Model Learning from Published Aggregated Data. Learning Structure and Schemas from Documents 2011: 369-384 - 2010
- [c11]Bartlomiej Sniezynski, Wojciech Wójcik, Jan D. Gehrke, Janusz Wojtusiak:
Combining Rule Induction and Reinforcement Learning: An Agent-based Vehicle Routing. ICMLA 2010: 851-856 - [p1]Janusz Wojtusiak, Kenneth A. Kaufman:
Ryszard S. Michalski: The Vision and Evolution of Machine Learning. Advances in Machine Learning I 2010: 3-22
2000 – 2009
- 2009
- [j3]Janusz Wojtusiak:
The LEM3 System for Multitype Evolutionary Optimization. Comput. Informatics 28(2): 225-236 (2009) - [j2]Jacek M. Zurada, Maciej A. Mazurowski, Rommohan Ragade, Artur Abdullin, Janusz Wojtusiak, James E. Gentle:
Building virtual community in computational intelligence and machine learning [Research Frontier]. IEEE Comput. Intell. Mag. 4(1): 43-54 (2009) - [j1]Janusz Wojtusiak
Towards application of rule learning to the meta-analysis of clinical data: An example of the metabolic syndrome. Int. J. Medical Informatics 78(12): 104-111 (2009) - 2008
- [c10]Jan D. Gehrke, Janusz Wojtusiak:
Traffic Prediction for Agent Route Planning. ICCS (3) 2008: 692-701 - [c9]Jacek M. Zurada, Janusz Wojtusiak, Fahmida Chowdhury, James E. Gentle, Cedric J. Jeannot, Maciej A. Mazurowski:
Computational intelligence virtual community: Framework and implementation issues. IJCNN 2008: 3153-3157 - 2007
- [c8]Janusz Wojtusiak, Ryszard S. Michalski, Thipkesone Simanivanh, Anna V. Baranova:
The Natural Induction System AQ21 and its Application to Data Describing Patients with Metabolic Syndrome: Initial Results. ICMLA 2007: 518-523 - [c7]Ryszard S. Michalski, Janusz Wojtusiak:
Generalizing Data in Natural Language. RSEISP 2007: 29-39 - 2006
- [c6]Janusz Wojtusiak, Ryszard S. Michalski:
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems. GECCO 2006: 1281-1288 - [c5]Ryszard S. Michalski, Janusz Wojtusiak, Kenneth A. Kaufman:
Intelligent Optimization via Learnable Evolution Model. ICTAI 2006: 332-335 - [c4]Janusz Wojtusiak, Ryszard S. Michalski, Kenneth A. Kaufman, Jaroslaw Pietrzykowski:
The AQ21 Natural Induction Program for Pattern Discovery: Initial Version and its Novel Features. ICTAI 2006: 523-526 - [c3]Janusz Wojtusiak, Ryszard S. Michalski:
The Use of Compound Attributes inAQ Learning. Intelligent Information Systems 2006: 189-198 - [c2]Ryszard S. Michalski, Kenneth A. Kaufman, Jaroslaw Pietrzykowski, Bartlomiej Sniezynski, Janusz Wojtusiak:
Learning Symbolic User Models for Intrusion Detection: A Method and Initial Results. Intelligent Information Systems 2006: 273-285 - [c1]Kenneth A. Kaufman, Ryszard S. Michalski, Jaroslaw Pietrzykowski, Janusz Wojtusiak:
An Integrated Multi-task Inductive Database VINLEN: Initial Implementation and Early Results. KDID 2006: 116-133
Coauthor Index
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last updated on 2024-10-21 20:30 CEST by the dblp team
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