# Parallel-Based Corpus Annotation for Malay Health Documents
## 4 Corpus Malay Health Document  
The Malay Health Document Annotated Corpus, a detailed collection of annotated health documents, is a crucial asset for researchers and practitioners focusing on the Malay language. It facilitates the training and evaluation of named entity recognition (NER) models specifically crafted for Malay. These models excel in accurately extracting pertinent information from Malay health documents, benefiting medical research, clinical text analysis, and electronic health record management. Moreover, this corpus plays a pivotal role in advancing various natural language processing (NLP) technologies in healthcare, such as natural language understanding, \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Malay Text**} & \multicolumn{4}{c}{**Manually Annotated**} \\ \cline{2-4}  & **Penyakit** & **Simptom** & **Rawatan** \\ \hline Infarksi miokardium akut (serangan jantung akut) biasanya disebabkan oleh darah beku. & Infarksi miokardium akut & \\ \hline Darah beku ini yang menyebabkan & & & \\ pengaliran darah terhenti ke sebahagian & & Darah beku & \\ \cline{2-4} daripada otot jantung. & & & \\ \cline{2-4} Apa yang menyebabkan infarksi & & & \\ mikocardium? Penyebab Utama infarksi & & & \\ mikocardium adalah darah beku (trombosis) & & & \\ \cline{2-4} yang terbentuk dialam anteri koronari & & & \\ \cline{2-4} utama, atau salah satu daripada & & & \\ \cline{2-4} cabang-cabangnya. & & & \\ \hline Apakah gejala–gejala infarksi miokardium? & & & \\ Gejala yang paling biasa adalah sakit dada & & & \\ \cline{2-4} yang teruk, yang sering terasa seperti & & & \\ \cline{2-4} tekanan berat di dada. & & & \\ \hline Walau bagaimanapun, eseetengah orange & & & \\ hanya mempunyai ketidakselesaan ringan di & & & Ketidakselesaan \\ dada mereka atau merasa seperti senak atau & & & \\ \cline{2-4} pedih ulu hati. & & & \\ \cline{2-4} Kadangkala infarksi myokardium boleh & & & \\ \cline{2-4} menyebabkan kematian mengejut tetapi & & & \\ \cline{2-4} keadaan ini jarang berlaku. & & & \\ \hline Apakah Rawatan untuk infarksi & & & \\ \cline{2-4} miokardium? Terdapat du rawatan yang & & & \\ \cline{2-4} boleh memulihkan aliran darah yang & & & \\ \cline{2-4} tersumbat: Angiol plastid kecemasan. & & & \\ \cline{2-4} Ini adalah rawatan yang terbaik jika ia boleh & & & \\ \cline{2-4} didapati dan boleh dilakukan dalam & & & \\ \cline{2-4} beberapa jam gejala bermula. & & & \\ \hline Suntikan ubat cair darah adalah alternatif & & & \\ \cline{2-4} kepada angiol plastid kecemasan. & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Examples result in annotated Malay text. sentiment analysis, and text classification. It covers a wide array of health-related entities, including diseases, symptoms, and treatments, thus thoroughly representing the healthcare sector, encompassing medical, pharmaceutical, and clinical research areas. The utilization of this corpus not only enhances the effectiveness of NER models in discerning and retrieving valuable data from Malay-language health documents but also aids in expanding the scope and efficiency of NLP technologies within the healthcare field. This amplifies their applicability and utility in diverse scenarios like medical research and clinical text analysis (see Figure 2.)  
The primary result of this research is the creation of the Malay Health Document Annotated Corpus, which is derived from both English and Malay health documents. The corpus contains a diverse set of accurately labeled health-named entities, such as penyakit (diseases), symptom (symptons), and rawatan (treatments). These entities can be seen in Table 7, which provides descriptions and examples for each entity type. The development of the Malay Health Document Annotated Corpus significantly contributes to the growing body of NLP resources for the Malay language. By providing a comprehensive annotated corpus, researchers are enabled to develop and evaluate NER models that can accurately analyze Malay health documents. This ultimately leads to better health outcomes for Malay speakers.