Sadid A. Hasan
- Health Informatics top 5%
- Artificial Intelligence top 2%
- Topic Modeling 39
- Natural Language Processing Techniques 27
- Advanced Text Analysis Techniques 13
- Machine Learning in Healthcare 8
- Semantic Web and Ontologies 4
- Toxicology top 10%
-
- Multimodal Machine Learning Applications 5
- Advanced Image and Video Retrieval Techniques 2
- Health Information Management top 10%
-
- Biomedical Text Mining and Ontologies 18
- Co-authors
- Yllias ChaliOladimeji FarriLing YuanJoey LiuKathy LeeAshequl QadirVivek V. DatlaMatthew P. Lungren
- Journals
- Information Processing & Management (2 papers)Computational Linguistics (1 paper)Artificial Intelligence in Medicine (1 paper)
- Partner nations
- United StatesCanadaFinland
In The Last Decade
Sadid A. Hasan
43 papers receiving 746 citations
Peers
Comparison fields: 5 of 103
- Health Informatics 32
- Artificial Intelligence 620
- Toxicology 27
- Computer Vision and Pattern Recognition 116
- Health Information Management 23
Countries citing papers authored by Sadid A. Hasan
This map shows the geographic impact of Sadid A. Hasan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sadid A. Hasan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sadid A. Hasan more than expected).
Fields of papers citing papers by Sadid A. Hasan
This network shows the impact of papers produced by Sadid A. Hasan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sadid A. Hasan. The network helps show where Sadid A. Hasan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sadid A. Hasan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 16 | |
| 2 | 2020 | 74 | |
| 3 | Overview of the VQA-Med Task at ImageCLEF 2020: Visual Question Answering and Generation in the Medical Domain. | 2020 | 26 |
| 4 | 2019 | 4 | |
| 5 | Overview of ImageCLEF 2018 Medical Domain Visual Question Answering Task. | 2018 | 26 |
| 6 | Towards Dataset Creation And Establishing Baselines for Sentence-level Neural Clinical Paraphrase Generation and Simplification. | 2018 | 5 |
| 7 | Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study | 2017 | 18 |
| 8 | PRNA at ImageCLEF 2017 Caption Prediction and Concept Detection Tasks. | 2017 | 9 |
| 9 | Learning to Diagnose: Assimilating Clinical Narratives using Deep Reinforcement Learning | 2017 | 10 |
| 10 | Open domain real-time question answering based on asynchronous multiperspective context-driven retrieval and neural paraphrasing. | 2017 | 2 |
| 11 | A Hybrid Approach to Precision Medicine-related Biomedical Article Retrieval and Clinical Trial Matching. | 2017 | 2 |
| 12 | Assorted Textual Features and Dynamic Push Strategies for Real-time Tweet Notification. | 2016 | 0 |
| 13 | Neural Clinical Paraphrase Generation with Attention | 2016 | 16 |
| 14 | Clinical Question Answering using Key-Value Memory Networks and Knowledge Graph. | 2016 | 4 |
| 15 | Open Domain Real-Time Question Answering Based on Semantic and Syntactic Question Similarity. | 2016 | 3 |
| 16 | Using Neural Embeddings for Diagnostic Inferencing in Clinical Question Answering. | 2015 | 7 |
| 17 | On the Effectiveness of Using Syntactic and Shallow Semantic Tree Kernels for Automatic Assessment of Essays | 2013 | 2 |
| 18 | Towards Automatic Topical Question Generation | 2012 | 17 |
| 19 | On the Effectiveness of using Sentence Compression Models for Query-Focused Multi-Document Summarization | 2012 | 17 |
| 20 | Using Syntactic and Shallow Semantic Kernels to Improve Multi-Modality Manifold-Ranking for Topic-Focused Multi-Document Summarization | 2011 | 1 |
About Sadid A. Hasan
Sadid A. Hasan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Toxicology, having authored 46 papers that have together received 803 indexed citations. Recurring topics across this work include Topic Modeling (39 papers), Natural Language Processing Techniques (27 papers), Biomedical Text Mining and Ontologies (18 papers), Advanced Text Analysis Techniques (13 papers), Machine Learning in Healthcare (8 papers), Multimodal Machine Learning Applications (5 papers), Semantic Web and Ontologies (4 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Health Informatics (32 citations), Artificial Intelligence (620 citations) and Toxicology (27 citations). Sadid A. Hasan has collaborated with scholars based in United States, Canada and Finland. Frequent co-authors include Yllias Chali, Oladimeji Farri, Ling Yuan, Joey Liu, Kathy Lee, Ashequl Qadir, Vivek V. Datla, Matthew P. Lungren, N Moradzadeh and Brian E. Chapman. Their work appears in journals such as Information Processing & Management, Computational Linguistics and Artificial Intelligence in Medicine.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.