HausaNLP at SemEval-2023 Task 12: Leveraging African Low Resource TweetData for Sentiment Analysis

We present the findings of SemEval-2023 Task 12, a shared task on sentiment analysis for low-resource African languages using Twitter dataset. The task featured three subtasks; subtask A is monolingual sentiment classification with 12 tracks which are all monolingual languages, subtask B is multilingual sentiment classification using the tracks in subtask A and subtask C is a zero-shot sentiment classification. We present the results and findings of subtask A, subtask B and subtask C. We also release the code on github. Our goal is to leverage low-resource tweet data using pre-trained Afro-xlmr-large, AfriBERTa-Large, Bert-base-arabic-camelbert-da-sentiment (Arabic-camelbert), Multilingual-BERT (mBERT) and BERT models for sentiment analysis of 14 African languages. The datasets for these subtasks consists of a gold standard multi-class labeled Twitter datasets from these languages. Our results demonstrate that Afro-xlmr-large model performed better compared to the other models in most of the languages datasets. Similarly, Nigerian languages: Hausa, Igbo, and Yoruba achieved better performance compared to other languages and this can be attributed to the higher volume of data present in the languages

Morbidity and mortality profile of patients seen in medical emergency unit of a Teaching Hospital in Nigeria: A 4-year audit

Background: Ahmadu Bello University Teaching Hospital (ABUTH) Zaria is strategically located to serve as referral center for most stable and emergency cases in the northwestern part of Nigeria. Patients also come on self-referral. Objective: This study aimed to describe the pattern of medical presentation and outcomes at the emergency unit of ABUTH over a 4-year period. Materials and Methods: A review of medical admissions into the Emergency unit of ABUTH, Zaria, between January 2013 and December 2016 was carried out using the case records of patients as well as register of admissions and discharges, information obtained were entered into a predetermined questionnaire. Results: The patients admitted during the period numbered 5193, with age range of 15–92 years. There were 2895 (56.0%) males and 2298 (44.0%), with a male-to-female ratio of 1.3:1. Emergencies attributable to infectious diseases occurred with the highest frequency (20.6%), followed by gastrointestinal (20.5%), renal (14.5%), endocrine (13.8%), respiratory (12.4%), cardiac (9%), neurological (2.8%), and hematological (1.1%). There was a significantly (P < 0.001) higher occurrence of noncommunicable diseases (71.5%) than communicable diseases (28.5%), as well as higher male cases in renal, respiratory, hematological emergencies (P < 0.05). There were more admissions in the wet season, (April to September) while the October to January period consistently recorded the low admission rates. An increasing trend in emergency medical admissions was observed, being highest in the year 2016. The median duration of stay was 4.5 days (range of 0–12 days). The outcomes of admission revealed 470 (9%) deaths, 2012 (37%) direct discharges, and 2801 (54%) transfers to male or female medical wards. Cases of tetanus had the highest case fatality rate (45%) while hypertensive emergencies had the lowest (4%). Conclusion: There is a rising trend of communicable as opposed to non-communicable diseases' emergencies in Zaria. Of the non-communicable diseases, incidence of gastro-intestinal emergencies was the highest while that of haematology was the least. The intra-hospital mortality rate attributable to medical emergencies is relatively lower in Zaria