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ORCIDTransAI 2022: Laguna Hills, CA, USA
- Fourth International Conference on Transdisciplinary AI, TransAI 2022, Laguna Hills, CA, USA, September 19-21, 2022. IEEE 2022, ISBN 978-1-6654-7184-8
- Delaram Golpayegani, Joshua Hovsha
, Leon W. S. Rossmaier, Rana Saniei, Jana Misic:
Towards a Taxonomy of AI Risks in the Health Domain. 1-8 - Hana Ahmed, Roselyne Tchoua, Jay F. Lofstead:
Measuring Reproduciblity of Machine Learning Methods for Medical Diagnosis. 9-16 - Hilda Goins, Mohd Anwar:
Data-driven Assessment of Dementia Caregivers' Burden: One size does not fit all. 17-21 - Dillam Jossue Diaz Romero, Isiah Zaplana, Simon Van den Eynde, Wouter Sterkens, Toon Goedemé, Jef Peeters:
Enhanced Plastic Recycling using RGB+Depth Fusion with MassFaster and MassMask R-CNN. 22-29 - Akshata Tiwari:
Effectiveness of Deep Learning for Erasing Satellite Streaks in Astronomical Photos. 30-31 - Yue Zhan, Michael S. Hsiao:
A Hybrid Approach for Automatic Feedback Generation in Natural Language Programming. 32-39 - Tejaswani Verma, Christoph Lingenfelder, Dietrich Klakow:
Generating Natural Language Explanations for Black-Box Predictions. 40-46 - Charlotte Lew:
Neural Network Modeling of HIV Acute and Chronic Phases With and Without Antiretroviral Intervention. 47-54 - Yang Liu, Mohd Anwar:
Learning Programming in Social Media: An NLP-powered Reddit Study. 55-58 - Michael Williamson, Taehyung Wang:
Leveraging Differences in Entropy for Password Generating Models. 59-62 - Paulo Shakarian, Gerardo I. Simari:
Extensions to Generalized Annotated Logic and an Equivalent Neural Architecture. 63-70 - Adam Craig, Carl Taswell:
Inclusion and Exclusion Criteria for Automating Adherence to Scope of Conference Calls for Papers. 71-74 - Romi Goldner Kabeli, Sol Efroni:
A Language Model identifies population-level features of the T cell Receptor via self-supervised learning. 75-78 - Aashish Cheruvu:
Multimodal Recommender System in the Prediction of Disease Comorbidity. 79-82 - Yassine Belkhouche:
A language processing-free unified spam detection framework using byte histograms and deep learning. 83-86 - Thi Bui, Katerina Potika:
Twitter Bot Detection using Social Network Analysis. 87-88 - Abdul Matin, Samuel Armstrong, Saptashwa Mitra, Shrideep Pallickara, Sangmi Lee Pallickara:
Rapid Betweenness Centrality Estimates for Transportation Networks using Capsule Networks. 89-96 - Minori Endo, Pauline N. Kawamoto:
Tuning Small Datasets for a Custom Apple Sorting System based on Deep Learning. 97-100 - May Almousa, Ruben Furst, Mohd Anwar:
Characterizing Coding Style of Phishing Websites Using Machine Learning Techniques. 101-105 - Sarah Saad, Thomas Palazzolo, Chencheng Zhang, Robert G. Reynolds, Ashley Lemke, John O'Shea, Cailen O'Shea:
Learning to Evolve Procedural Content in Games Using Cultural Algorithms. 106-115 - Lars Quakulinski, Adamantios Koumpis, Oya Deniz Beyan:
Establishing Transparency in Artificial Intelligence Systems. 116-121 - Edward Xu, Thiruvarangan Ramaraj, Roselyne Tchoua, Jacob Furst, Daniela Raicu:
Contextualizing Lung Nodule Malignancy Predictions with Easy vs. Hard Image Classification. 122-127 - Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen, Murali Emani, Hailu Xu:
Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study. 128-134 - Joseph R. Barr, Toby Dylan Hocking, Garinn Morton, Tyler Thatcher, Peter Shaw:
Classifying Imbalanced Data with AUM Loss. 135-141 - Joseph R. Barr, Peter Shaw, Faisal N. Abu-Khzam, Tyler Thatcher, Toby Dylan Hocking:
Graph Embedding: A Methodological Survey. 142-148 - Toby Dylan Hocking, Joseph R. Barr, Tyler Thatcher:
Interpretable linear models for predicting security vulnerabilities in source code. 149-155 - Jon C. Haass:
Cyber Threat Intelligence and Machine Learning. 156-159
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