NLP | Mohammed Khalilia (محمد عبد الستار قاسم)

Synthetic Panels

Sat, 11 Jan 2025 00:00:00 +0000

Recruiting the right participants for a study can be difficult. You may not get the exact demographics you need, and the shorter the deadline, the less sure you can be that everyone will answer on time. One possible solution can be to use synthetic panels.

Synthetic panels are powered by a first party proprietary AI model developed here at Qualtrics. Our synthetic panel is trained on thousands of responses from a variety of demographic backgrounds in order to more accurately predict how certain populations would respond to a survey.

Service architecture for entity and relationship detection in unstructured text

Tue, 01 Nov 2022 00:00:00 +0000

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Wojood - Arabic NER

Sat, 01 Jan 2022 00:00:00 +0000

Wojood consists of about 550K tokens (MSA and dialect) that are manually annotated with 21 entity types (e.g., person, organization, location, event, date, etc). It covers multiple domains and was annotated with nested entities. The corpus contains about 75K entities and 22.5% of which are nested. A nested named entity recognition (NER) model based on BERT was trained (F1-score 88.4%).

Comprehend Medical

Thu, 11 Jan 2018 00:00:00 +0000

Amazon Comprehend Medical is a HIPAA-eligible natural language processing (NLP) service that uses machine learning that has been pre-trained to understand and extract health data from medical text, such as prescriptions, procedures, or diagnoses.