Mobile application for caregiver in collecting statistical data of BPSD attack focused on macro activities

Hamdhana, Defry

doi:10.1145/3384419.3430577

Cited by 1 publication

(1 citation statement)

References 3 publications

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“…In the modern world, the number of elderly people is increasing significantly [1], which means that they need special care [2], such as facilities that are specifically designed for parents or caregivers who are assigned to assist the elderly in carrying out their daily lives and assisting them with their daily tasks. In some cases, there are conditions in which the elderly are unable to recognize what their need, have difficulty achieving daily necessities, or have a hard time communicating what they really want or need [8]. It is common for them to have this condition, which can cause them to be irritable and aggressive easily, be depressed easily, and to even be angry at people [3].…”

Section: Introductionmentioning

confidence: 99%

Obtaining Elderly Patients’ Lifestyle Information from Unstructured Text Sources

Hamdana

Husna

2023

Proceedings of Malikussaleh International Conference on Multidi

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In this work, we made many simulations to take information from free-text notes belonging to the patient that indicates his or her habits. Detailed information about a patient's habits will allow the nurse to create a personalized daily schedule. Due to the fact that each patient has a different routine. The information is separated into five categories: dietary habits, drinking/smoking habits, excretion habits/toilet style, fashionable/colour preference/footwear, and favourite music/radio/TV shows. To realize this, we use six machine learning models, there are Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Multinomial Logistic Regression (MLR), and Gradient Boosting (GB). As a result, all models have more than 90% accuracy on both train sets and test sets.In this study, we focus on SVM with Train Set Accuracy score 93.9% and Test Set Accuracy score 94.1%, which is more resistant to overfitting issues.

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Section: Introductionmentioning

confidence: 99%