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How Successful Is Transfer Learning for Detecting Anorexia on Social Media?

Pilar López-Úbeda, Flor Miriam Plaza-del-Arco, Manuel Carlos Díaz-Galiano, Maria-Teresa Martín-Valdivia
2021 Applied Sciences  
Natural Language Processing, a branch of artificial intelligence, has the potential to contribute towards early anorexia detection in textual data.  ...  The main contribution of this paper is the application of transfer learning techniques using Transformer-based models for detecting anorexia in tweets written in Spanish.  ...  types of diseases and detect them early.  ... 
doi:10.3390/app11041838 fatcat:fddadtr6t5ap7eucebpf3xmduq

Detection of Anorexic Girls-In Blog Posts Written in Hebrew Using a Combined Heuristic AI and NLP Method

Yaakov Hacohen-Kerner, Natan Manor, Michael Goldmeier, Eytan Bachar
2022 IEEE Access  
The construction of this dataset was supervised and approved by an international expert on anorexia.  ...  We tested several text classification (TC) methods, using various feature sets (content-based and style-based), five machine learning (ML) methods, three RNN models, four BERT models, three basic preprocessing  ...  In 2018 and 2019, eRisk organized tasks related to the early detection of anorexia.  ... 
doi:10.1109/access.2022.3162685 fatcat:e7ihdovqbfchbli7cxod57wo5a

Overview of eRisk at CLEF 2019: Early Risk Prediction on the Internet (extended overview)

David E. Losada, Fabio Crestani, Javier Parapar
2019 Conference and Labs of the Evaluation Forum  
Two of them shared the same format and focused on early detecting signs of depression (T1) or self-harm (T2).  ...  The main purpose of eRisk is to explore issues of evaluation methodology, effectiveness metrics and other processes related to early risk detection.  ...  We also thank the financial support obtained from the i) "Ministerio de Ciencia, Innovación y Universidades" of the Government of Spain (research grants RTI2018-093336-B-C21 and RTI2018-093336-B-C22),  ... 
dblp:conf/clef/LosadaCP19 fatcat:ku5ou6kzzzfzxhsytiznqobdb4

MellisAI - An AI Generated Music Composer Using RNN-LSTMs

N. Hari Kumar, Ericsson Research Labs, Ericsson, India, P. S Ashwin, Haritha Ananthakrishnan
2020 International Journal of Machine Learning and Computing  
LSTM models were used for creating four different modules namely, the Tune module, the Motif module, the Endnote module, and the Gamaka module.  ...  It implements the task of automated musical composition using a pipeline where various key features of the resultant tune are constructed separately step by step and finally combined into a complete piece  ...  Vedavalli gave us an insight about how to further elaborate our data set with different kinds of songs and ragas and encouraged us to take the implementation further, while Mr.  ... 
doi:10.18178/ijmlc.2020.10.2.927 fatcat:k6fu27qdcnd7vdodagzb7srn2a

Assessment of Machine Learning Techniques in IoT-Based Architecture for the Monitoring and Prediction of COVID-19

Abdullah Aljumah
2021 Electronics  
The proposed system utilizes the Internet of Things (IoT) platform to capture users' time-sensitive symptom information to detect potential cases of coronaviruses early on, to track the clinical measures  ...  adopted by survivors, and to gather and examine appropriate data to verify the existence of the virus.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/electronics10151834 fatcat:byb7npucdfgwraksqrftldivfa

Investigating Machine Learning & Natural Language Processing Techniques Applied for Predicting Depression Disorder from Online Support Forums: A Systematic Literature Review

Isuri Anuradha Nanomi Arachchige, Priyadharshany Sandanapitchai, Ruvan Weerasinghe
2021 Information  
Our objective is to undertake a systematic review of the literature on NLP and ML approaches used for depression identification on Online Support Forums (OSF).  ...  For the purpose of the review, 29 articles were selected and analysed.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/info12110444 fatcat:buft2xvmaba65dmghesdljd7xq

Progress in Deep Learning Mechanisms for Information Extraction Social Networks: An Expository Overview

Israel Fianyi, Gifty Andoh Appiah
2021 International Journal of Computer Applications  
Incidentally, social networks and other related online platforms are known to hold a copious amount of unstructured user-generated content.  ...  The paper is designed to help non-expert researchers comprehend the fundamentals of deep learning and Natural Language Processing methods for Information Extraction.  ...  Furthermore, Ramírez-Cifuentes, Mayans [44] used social media data to determine the risk associated with the early detection of anorexia.  ... 
doi:10.5120/ijca2021921155 fatcat:qzneg7npn5d5hocznq53oyek6y

Explainable Depression Detection with Multi-Modalities Using a Hybrid Deep Learning Model on Social Media [article]

Hamad Zogan, Imran Razzak, Xianzhi Wang, Shoaib Jameel, Guandong Xu
2021 arXiv   pre-print
We have considered user posts along with Twitter-based multi-modal features, specifically, we encode user posts using two levels of attention mechanisms applied at the tweet-level and word-level, calculate  ...  In this work, we propose interpretive Multi-Modal Depression Detection with Hierarchical Attention Network MDHAN, for detection depressed users on social media and explain the model prediction.  ...  Models such as BiGRU, GRU, and LSTM fall in the class of RNNs. The static attributes are usually inputted to the BiGRU.  ... 
arXiv:2007.02847v2 fatcat:4y4xl7rysfdqtfj3pojqxk6zo4

Modern Views of Machine Learning for Precision Psychiatry [article]

Zhe Sage Chen, Prathamesh Kulkarni, Isaac R. Galatzer-Levy, Benedetta Bigio, Carla Nasca, Yu Zhang
2022 arXiv   pre-print
In light of the NIMH's Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and  ...  Advanced wearable and mobile technologies also call for the new role of ML/AI for digital phenotyping in mobile mental health.  ...  Acknowledgments The research was partially supported from the US National Science Foundation (CBET-1835000 to Z.S.C.), the National Institutes of Health (R01-NS121776 and R01-MH118928 to Z.S.C.).  ... 
arXiv:2204.01607v2 fatcat:coo557v2jzh6debycy3mhccfze

Utilizing Neural Networks and Linguistic Metadata for Early Detection of Depression Indications in Text Sequences

Marcel Trotzek, Sven Koitka, Christoph M. Friedrich
2018 IEEE Transactions on Knowledge and Data Engineering  
This paper addresses the early detection of depression using machine learning models based on messages on a social platform.  ...  An ensemble of both approaches is shown to achieve state-of-the-art results in a current early detection task.  ...  The fields of depression detection and early detection were first combined by the publication of a dataset for early detection of depression in reddit messages [53] and research using this dataset was  ... 
doi:10.1109/tkde.2018.2885515 fatcat:j453v3rur5bnvgrvos5ogslqhy

"You Know What to Do": Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks

Enrico Mariconti, Guillermo Suarez-Tangil, Jeremy Blackburn, Emiliano De Cristofaro, Nicolas Kourtellis, Ilias Leontiadis, Jordi Luque Serrano, Gianluca Stringhini
2018 Zenodo  
Then, we use an ensemble of classifiers to determine the likelihood that a video will be raided with high accuracy (AUC up to 94%).  ...  Overall, our work paves the way for providing video platforms like YouTube with proactive systems to detect and mitigate coordinated hate attacks.  ...  This project has received funding from the European Union's Horizon 2020 Research and Innovation program under the Marie Skłodowska-Curie ENCASE project (GA No. 691025).  ... 
doi:10.5281/zenodo.1479939 fatcat:i6ojj6smgbdyhiqa3hv4aodgze

"You Know What to Do": Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks [article]

Enrico Mariconti, Guillermo Suarez-Tangil, Jeremy Blackburn, Emiliano De Cristofaro, Nicolas Kourtellis, Ilias Leontiadis, Jordi Luque Serrano, Gianluca Stringhini
2019 arXiv   pre-print
Then, we use an ensemble of classifiers to determine the likelihood that a video will be raided with very good results (AUC up to 94%).  ...  Overall, our work provides an important first step towards deploying proactive systems to detect and mitigate coordinated hate attacks on platforms like YouTube.  ...  This project has received funding from the European Union's Horizon 2020 Research and Innovation program under the Marie Skłodowska-Curie ENCASE project (GA No. 691025) and from the EPSRC (grant number  ... 
arXiv:1805.08168v3 fatcat:6ohyv3zswvdqrlhlka4tgfn6la

Machine learning and deep learning techniques to support clinical diagnosis of arboviral diseases: A systematic review

Sebastião Rogério da Silva Neto, Thomás Tabosa Oliveira, Igor Vitor Teixeira, Samuel Benjamin Aguiar de Oliveira, Vanderson Souza Sampaio, Theo Lynn, Patricia Takako Endo, Rhoel Ramos Dinglasan
2022 PLoS Neglected Tropical Diseases  
It should help physicians in their decision-making process and, consequently, improve the use of resources and the patient's quality of life.  ...  Conclusions The use of an efficient clinical decision support system for arboviral diseases can improve the quality of the entire clinical process, thus increasing the accuracy of the diagnosis and the  ...  on the promotion of Teaching, Research and Extension.  ... 
doi:10.1371/journal.pntd.0010061 pmid:35025860 pmcid:PMC8791518 fatcat:7s73o3qm3fgglp47lnrgwd5bja

"You Know What to Do": Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks

Enrico Mariconti, Guillermo Suarez-Tangil, Jeremy Blackburn, Emiliano De Cristofaro, Nicolas Kourtellis, Ilias Leontiadis, Jordi Luque Serrano, Gianluca Stringhini
2018 Zenodo  
Then, we use an ensemble of classifiers to determine the likelihood that a video will be raided with high accuracy (AUC up to 94%).  ...  Overall, our work paves the way for providing video platforms like YouTube with proactive systems to detect and mitigate coordinated hate attacks.  ...  Previous work has looked at the use of YouTube by LGBT users for self-disclosure [27] , for anti-or pro-anorexia [49] , fat stigmatization [32] , sharing violent content [67] , far-right propaganda  ... 
doi:10.5281/zenodo.1479940 fatcat:dd67w66sq5chvooupc3znh5f4u

Use of Transfer Learning for Automatic Dietary Monitoring through Throat Microphone Recordings

Mehmet Ali Tugtekin Turan, Engin Erzin
2019 Zenodo  
Then, we investigate the use of transfer learning paradigm in-depth to design an improved food intake detection and classification system.  ...  In this thesis, we first define an ADM system using a throat microphone (TM) food intake sound recordings, where chewing and swallowing detection is presented.  ...  Classifier We utilized the SVM classifier for the food intake classification.  ... 
doi:10.5281/zenodo.3841956 fatcat:ncalroecszg3hhpc45havcxhee
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