The scientific program includes the talks related to the individual tracks, a panel about mining adverse drug reactions, a keynote talk and a flash talks for selected posters. Detailed agenda is shown below
Monday, November 8, 2021
UTC (Universal)
EST
Session
2:30-2:40 pm
9:30-9:40 am
Opening remarks
2:40-3:55 pm
9:40-10:55 am
NLM-Chem Track: Full text Chemical Identification and Indexing in PubMed articles (Track 2) Chair: Zhiyong Lu
Overview of the NLM-CHEM track - Full-text Chemical Identification and Indexing in PubMed articles (Rezarta Islamaj, Robert Leaman)
Chemical detection and indexing in PubMed full text articles using deep learning and rule-based methods (João Figueira Silva)
Improving Tagging Consistency and Entity Coverage for Chemical Identification in Full-text Articles (Hyunjae Kim)
A BERT-Based Hybrid System for Chemical Identification and Indexing in Full-Text Articles (Arslan Erdengasileng)
Chemical Identification and Indexing in PubMed Articles via BERT and Text-to-Text Based Approaches (Virginia Adams)
Automatic extraction of medication names in tweets (Track 3)
Chair: Davy Weissenbacher
BioCreative VII – Track 3: Automatic Extraction of Medication Names in Tweets (Davy Weissenbacher)
NCU-IISR/AS-GIS: Detecting Medication Names in Imbalanced Twitter Data with Pretrained Extractive QA Model and Data-Centric Approach (Yu Zhang)
BCH-NLP at BioCreative VII Track 3 - medications detection in tweets using transformer networks and multi-task learning (Dongfang Xu)
Tuesday, November 9, 2021
UTC (Universal)
EST
Session
2:00-2:10 pm
9:00-9:10 am
Opening remarks
2:10-3:55 pm
9:10-10:55 am
DrugProt:Text mining drug/chemical-protein interactions (Track 1)
Chair: Antonio Miranda-Escalada
Overview of DrugProt BioCreative VII track: quality evaluation and large scale text mining of drug-gene/protein relations (Martin Krallinger, Antonio Miranda-Escalada)
Using Knowledge Base to Refine Data Augmentation for Biomedical Relation Extraction (WonJin Yoon)
Extracting Drug-Protein Interaction using an Ensemble of Biomedical Pre-trained Language Models through Sequence Labeling and Text Classification Techniques (Ling Luo)
Text Mining Drug-Protein Interactions using an Ensemble of BERT, Sentence BERT and T5 models (Xin Sui)
Humboldt @ DrugProt: Chemical-Protein Relation Extraction with Pretrained Transformers and Entity Descriptions (Leon Weber)
Does constituency analysis enhance domain-specific pre-trained BERT models for relation extraction? (Anfu Tang)
Text Mining Drug/Chemical-Protein Interactions using an Ensemble of BERT and T5 Based Models (Virginia Adams)
CU-UD: text-mining drug and chemical-protein interactions with ensembles of BERT-based models(Mehmet Efruz Karabulut)
TTI-COIN at BioCreative VII Track 1 (Naoki Iinuma/Masaki Asada)
A Multi-Task Transfer Learning-based method for Extracting Drug-Protein Interactions (Ed-drissiya El-allaly)
lasigeBioTM at BioCreative VII Track 1: Text mining drug and chemical-protein interactions using biomedical ontologies (Diana Sousa)
Identifying Drug/chemical-protein Interactions in Biomedical Literature using the BERT-based Ensemble Learning Approach for the BioCreative 2021 DrugProt Track (Tzu-Yi Li)
Catalytic DS at BioCreative VII: DrugProt Track (Dennis Mehay)
Claim Detection in Biomedical Twitter Posts as a Prerequisite for Fact-Checking (Amelie Wührl)
Visual Exploration of Randomized Clinical Trials for COVID-19 (Abel Correa Dias)
COVID-SEE: The Scientific Evidence Explorer for COVID-19 Related Research (Karin Verspoor)
Long Covid: A Comprehensive Collection of Articles on Post-COVID Conditions (Robert Leaman)
Automated topic prediction of LitCovid using BioBERT (Vangala G Saipradeep)
A Survey of Relation Extraction Techniques Using Hybrid Classical and State of the Art Methods (Onur Kara)
Automatic Extraction of Medication Names in Tweets as Named Entity Recognition (Carole Anderson)
PubMedBERT-based Classifier with Data Augmentation Strategy for Detecting Medication Mentions in Tweets (Qing Hang)
Extraction of Medication Names from Twitter Using Augmentation and an Ensemble of Language Models (Igor Kulev)
Recognizing Chemical Entity in Biomedical Literature using a BERT-based Ensemble Learning Methods for the BioCreative 2021 NLM-Chem Track (Yu Wen Chiu)
Fine-tuning transformers for automatic chemical entity identification in PubMed articles (Robert Bevan)
PolyU CBS-NLP at BioCreative-VII LitCovid Task: Ensemble Learning for COVID-19 Multilabel Classification (Jinghang Gu)
Multi-label topic classification for COVID-19 literature annotation using an ensemble model based on PubMedBERT (Shubo Tian)
RobertNLP at the BioCreative VII - LitCovid track: Neural Document Classification Using SciBERT (Friedrich Annemarie)
TTI-COIN at BioCreative VII Track 2 (Tomoki Tsujimura)
Chemical–protein relation extraction in PubMed abstracts using BERT and neural networks (Rui Antunes)
R-BERT-CNN: Drug-target interactions extraction from biomedical literature (Jehad Aldahdooh)
5:00-6:15 pm
12:00-1:15 pm
Panel: Challenges in mining adverse drug reactions
The BioCreative organizers have convened this panel to explore the possibility of a future BioCreative evaluation on mining adverse drug reactions (ADRs). The panel will explore challenges of mining ADRs, focusing on applications (e.g., post-market surveillance, early warning from tracking social media, predictive models of toxic endpoints for chemicals and drugs, pre-clinical and clinical research) and data sources (including their limitations and accessibility).
Chairs: Martin Krallinger, Lynette Hirschman
Panelists:
Dr. Martin Krallinger (Chair)
CDR Monica Muñoz, FDA CDER
Prof. Özlem Uzuner, George Mason University
Dr. Raul Rodriguez-Esteban, Roche Pharmaceutics
Prof. Graciela Gonzalez-Hernandez, U Pennsylvania Medical School
Wednesday, November 10, 2021
UTC (Universal)
EST
Session
2:30-2:40 pm
9:30-9:40 am
Opening remarks
2:40-3:55 pm
9:40-10:55 am
LitCovid track Multi-label topic classification for COVID-19 literature annotation (Track 5)
Chair: Rezarta Islamaj
BioCreative VII LitCovid Track: multi-label topic classification for COVID-19 literature annotation (Qingyu Chen)
Multic-label topic classification for COVID-19 literature with Bioformer (Fang Li)
Multi-label topic classification for COVID-19 literature annotation: A BioBERT-based feature enhancement approach (Wentai Tang)
BERT-based bagging-stacking for multi-topic classification (Loïc Rakotoson)
Multi-label Topic Classification for COVID-19 Literature Annotation using the BERT-based Ensemble Learning Approach for the BioCreative 2021 LitCovid Track (Sheng-Jie Lin)
