3 research outputs found
Data-driven triage: exploring AI models for predicting emergency department outcomes
No full textIntroduction: Machine learning has become a significant trend in the healthcare sector recently, and its capabilities appear promising. This study aims to develop and validate four machine learning models in predicting triage outcomes in emergency departments.
Methodology: A retrospective cohort study utilising electronic health records in the emergency department of a teaching hospital, with four machine learning models to be evaluated: Random Forest (RF), Gradient Boosted Decision Tree (GBDT), K-Nearest Neighbors (KNN), and XGBoost.
Results: A total of 312 emergency patient records were acquired. The scores for accuracy, precision recall, and F1-score were 100% for RF, GBDT, and XGBoost. The models are also able to predict
a few classes accurately, potentially improving the triage process. Respiratory rate has a high impact on the decision in triaging to actual_class_5, which is the red zone (resuscitation), with an R-value of 0.36. Diastolic blood pressure and systolic blood pressure have a high correlation, as evidenced by the R-value, 0.61. Respiratory rate has a negative impact on oxygen saturation and a positive impact on body temperature, with R-values -0.49 and 0.32, respectively.
Discussion: On the performance tests of accuracy, precision, recall, and F1-score, the models (RF, GBDT and XGBoost) scored 100% for each of the tests, indicating a perfect classifier. This result indicates the overall ability of the model to improve triage by classifying accurately, as supported by Aljubran et al.'s (2023) statement that machine learning is a promising tool for improving triage decision-making. According to Elhaj, Achour, Tania, & Aciksari, (2023), in these performance tests the models (KNN and RF) achieved the highest score overall from 9 models trained by the researchers with an accuracy of 89.1% and 88.5%, precision of 89.0% and 88.7%, recall of 89.1% and 88.7%, and F1-score of 89.0% and 88.6%, while the CatBoost model (accuracy = 0.930, recall = 0.915, precision = 0.930, F1-score = 0.930) is clinically excellent to be developed as suggested by Aljubran et al., (2023).
Conclusion: Machine learning models can accurately triage patients when properly trained covering the possible variations of variables presented during triage. A prospective study is needed
to evaluate the models' ability further
The Influence of al-Sahihayn on Popular Hadith Literatures: The Case of Khazinah al-AsrarJalilah al-Adhkar
No full textThe compilations of authentic hadith by alBukhari
(d. 870) and Muslim (d. 875) known
collectively as al-Sahihayn serve for the Sunnis
as the second highest source of religion after the
Quran. The stringent methods in hadith selection
and appraisal in these books have contributed
to their credibility and reliability as a primary
religious source, and many succeeding works
attempted to emulate them, though with varying
results. Some popular hadith literatures have
also utilized al-Sahihayn as their main source
of hadith quotation to enhance their status of
acceptance, notwithstanding some compromises
and modifications. This is particularly the case
with a 19th century hadith compilation known
as Khazinah al-Asrar Jalilah al-Adhkar by
Muhammad Haqqi al-Nazilli (d. 1884). Thus,
this paper aims to delve into this topic in
further details. It attempts to analyze the role
and influence of al-Sahihayn on Khazinah alAsrar,
the extent of compliance of its author
with the former, and the overall implication of
its extensive methodology on succeeding hadith
works, particularly in Southeast Asia
SISTEM PEMERIKSAAN ALAT PEMADAM KEBAKARAN PERSPEKTIF MILK AL DAULAH: STUDI PADA PEMADAM KEBAKARAN BANDA ACEH
No full textThe Banda Aceh City Fire and Rescue Service must ensure that fire extinguishers are well maintained and can be used at any time in an emergency. Fire extinguishers are state property that are useful for the community. Therefore, the author aims to conduct research to find out how fire extinguishers are inspected at the Banda Aceh City Fire and Rescue Service, as well as what Milk al Daulah's perspective is regarding checking fire extinguishers at the Banda Aceh City Fire and Rescue Service. This research uses a sociological juridical method with a qualitative research type, and data was obtained using interview techniques and documentation. Based on the research results, it was found that, first, inspection and maintenance of fire extinguishers at the Banda Aceh City Fire and Rescue Service was carried out by checking and warming up the engine, checking lubricants and fuel, checking the condition of tires, checking the braking system, checking equipment completeness. fire extinguisher, electrical system inspection, exterior maintenance, water tank drain, and vehicle roadworthiness test. Maintenance is carried out regularly at certain time intervals. Usually every 3 months, 6 months or 1 year. Depends on manufacturer's instructions, vehicle model and components used. Second, the Banda Aceh City Fire and Rescue Service is responsible for inspecting fire extinguishers. So that these tools function and are used properly when a fire disaster occurs. Maintaining fire extinguishers provides benefits to the community. The Banda Aceh city fire and rescue service as the regional government has done its job well in carrying out inspections of fire extinguishers, therefore this is in accordance with the concept of milk al-daula
