Clinical Decision Support System for Unani Medicine Practitioners

Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medicines Practitioners are lacking modern IT applications in their everyday clinical practices. An Online Clinical Decision Support System may address this challenge to assist apprentice Unani Medicines practitioners in their diagnostic processes. The proposed system provides a web-based interface to enter the patient's symptoms, which are then automatically analyzed by our system to generate a list of probable diseases. The system allows practitioners to choose the most likely disease and inform patients about the associated treatment options remotely. The system consists of three modules: an Online Clinical Decision Support System, an Artificial Intelligence Inference Engine, and a comprehensive Unani Medicines Database. The system employs advanced AI techniques such as Decision Trees, Deep Learning, and Natural Language Processing. For system development, the project team used a technology stack that includes React, FastAPI, and MySQL. Data and functionality of the application is exposed using APIs for integration and extension with similar domain applications. The novelty of the project is that it addresses the challenge of diagnosing diseases accurately and efficiently in the context of Unani Medicines principles. By leveraging the power of technology, the proposed Clinical Decision Support System has the potential to ease access to healthcare services and information, reduce cost, boost practitioner and patient satisfaction, improve speed and accuracy of the diagnostic process, and provide effective treatments remotely. The application will be useful for Unani Medicines Practitioners, Patients, Government Drug Regulators, Software Developers, and Medical Researchers.Comment: 59 pages, 11 figures, Computer Science Bachelor's Thesis on use of Artificial Intelligence in Clinical Decision Support System for Unani Medicine

Quality of Life Assessment in Intestinal Stoma Patients in the Saudi Population: A Cross-Sectional Study

Background: A stoma poses numerous physical, social, and psychological challenges and interferes with some religious practices, thus potentially negatively affecting the quality of life. In the contemporary era of stoma care, the study sought to assess this impact in a population with distinctive sociocultural characteristics. Methods: A modified City of Hope Quality of Life ostomy questionnaire was used to survey patients with intestinal stomas. The scoring was dichotomous on a 0 to 10 scale, where 0–3 indicated severe impact, 4–6 moderate, and 7–10 minimum. Statistical analysis involved Student’s t-test, one-way ANOVA, Spearman’s correlation, and multivariate linear regression. Results: There were 108 patients, with 59 males and 49 females. The mean age was 40.8 years. The overall quality of life score was 6, for the social domain 7, the physical domain 6, the psychological domain 5, and the spiritual domain 6. The stoma’s impact on the quality of life was severe in 2%, moderate in 61%, and minimal in 37% of patients. Young patients, women, and those with benign diseases or without a job had low scores. Furthermore, 90% of patients had difficulty performing religious activities. For the regression analysis, life quality predictors were dietary, religious, pouch and stoma site issues, leak, odor, diarrhea or constipation, depression, anxiety, and future and disease concerns. Conclusions: Despite advances in stoma care, stoma patients had multiple impediments to their life quality. These were mainly psychological, but the physical and religious ones were also significant. A holistic approach to managing stoma patients is thus needed to help them have fulfilling lives