# DATLMedQA: A Data Augmentation and Transfer Learning Based Solution for Medical Question Answering
## 3 Materials and Method  
### Dataset  
**Pretraining Dataset. ** In this paper, we used the disease knowledge dataset used in DiseaseBERT [41] for pretraining. The Medical Subject Headings (MeSH) disease and mental disorder branch was selected as the disease vocabulary. A total of 5853 target disease terms from MeSH were searched through Wikipedia articles and 14,617 paragraphs of disease knowledge were collected. The code and data for the dataset are provided in [17]. We used the training procedure proposed in DiseaseBERT [41]: disease knowledge infusion training, which augments BERT-like pretrained models with disease knowledge to achieve better performance in answering medical questions, medical inference, and disease name recognition. In the DiseaseBERT pretraining dataset, the extraction of S is as follows. Taking the first item in the first column of Table 1 as an example: \"hemorrhagic septicemia\" (disease) is the name of the disease, which is extracted from an article title on Wikipedia and \"diagnosis\" (aspect) is from a section title in that same Wikipedia article. Q is constructed by the disease and aspect in S. A is the answer to Q. Table 1 shows some examples of the disease knowledge dataset. \begin{table}
\begin{tabular}{c c c} \hline \hline \(\mathbf{S}\) & \(\mathbf{Q}\) & \(\mathbf{A}\) \\ \hline Hemorrhagic septicemia: & What are the diagnosis of & Diagnosis on bases of blood \\ diagnosis & hemorrhagic septicemia? & smear and clinical findings. \\ \hline Hemorrhagic septicemia: & What are the treatments of & Sulphadimagine 100 mL \\ treatments & hemorrhagic septicemia? & orally and injection of \\ oxytetracycline 40 mL for & & \\  & & 3 days continuously. \\ \hline Microsporidiosis: diagnosis & What are the diagnosis of & The best option for diagnosis \\  & microsporidiosis? & is using pcr. \\ \hline Microsporidiosis: treatments & What are the treatments of & The best option for diagnosis \\  & microsporidiosis? & is using pcr. \\ \hline Hemorrhagic septicemia : & What are the treatments of & Fumagillin has been used in \\ treatments & hemorrhagic septicemia? & the treatment. another agent \\  & & used is albendazole. \\ \hline...... &...... &...... \\ \hline Ego: general & What is ego? & Ego or ego may refer to: \\ \hline Borderline leprosy: general & What is borderline leprosy? & Borderline leprosy is a \\  & & cutaneous skin condition with \\  & & numerous skin lesions that are \\  & & red irregularly shaped \\  & & plaques. \\ \hline Synovial chondomatosis: & what is synovial & Synovial chondomatosis is a \\ general & chondomatosis? & disease affecting the \\  & & synovium, a thin flexible \\  & & membrane around a joint. \\ \hline Priapism: physiology & What are the physiology of & The mechanisms are poorly \\  & & understood but involve \\  & & complex neurological and \\  & & vascular factors. \\ \hline Acute myeloid leukemia: & What are the symptoms of & Image:amlcase- \\  & acute myeloid leukemia? & 66.jpg! thumb! upright. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Disease knowledge dataset examples. submitted to the National Library of Medicine (NLM). The NLM is on the NIH campus and it is the world's largest biomedical library, leading the research, development, and training in biomedical informatics and health information technology. There are more than 100,000 requests submitted to the NLM every year, including over 10,000 consumer health questions (CHQs). CHQs cover a broad range of questions related to diseases, medications, or medical procedures. The NLM also constructs relevant resources by manually annotating relevant question elements. Table 4 shows several examples of consumer health questions. The first CHQ asks about the treatment of a disease (retinitis pigmentosa) and includes a lot of descriptive and personal information. The second CHQ is about a problem (\"abetalipoproteinemia\") and multiple questions. The third CHQ asks about ingredients in a medicine (Kapvay).