An all-inclusive and accurate prediction of outcomes for patients with acute ischemic stroke (AIS) is crucial clinical decision-making. This study developed extreme gradient boosting (XGBoost)-based models using three simple factors-age, fasting glucose, National Institutes Health Stroke Scale (NIHSS) scores-to predict the three-month functional after AIS. We retrieved medical records 1848 diagnosed AIS managed at a single center between 2016 2020. validated predictions ranked importance...

Introduction Assisted reproductive technology has been proposed for women with infertility. Moreover, in vitro fertilization (IVF) cycles are increasing. Factors contributing to successful pregnancy have widely explored. In this study, we used machine learning algorithms construct prediction models clinical pregnancies IVF. Materials and methods A total of 24,730 patients entered IVF intracytoplasmic sperm injection outcomes at Taipei Medical University Hospital. Data included patient...

Abstract Background Dengue fever is a well-studied vector-borne disease in tropical and subtropical areas of the world. Several methods for predicting occurrence dengue Taiwan have been proposed. However, to best our knowledge, no study has investigated relationship between air quality indices (AQIs) Taiwan. Results This aimed develop prediction model which meteorological factors, vector index, AQIs were incorporated into different machine learning algorithms. A total 805 records from 2013...

Chemotherapy plays an important role in the treatment of optic pathway hypothalamic gliomas (OPHGs). Commonly used regimens include carboplatin and vincristine monotherapy with vinblastine weekly. In this retrospective study, we a monthly regimen to treat progressive/recurrent OPHGs evaluated their effectiveness, visual preservation, toxicity. The study involved patients OPGH who were treated once per month. response, disease progression, overall survival, vision changes, toxicity recorded...

<title>Abstract</title> <bold>Background:</bold> Taiwan has a high caesarean section (CS) rate, ranging from 37% to 38%. Vaginal Birth After Cesarean (VBAC) offers potential solution reduce these rates. However, the prevalence of VBAC remains below 0.5%, primarily due concerns about risks adverse maternal and perinatal outcomes. <bold>Objectives:</bold> This study aims evaluate predictive performance various machine learning (ML) models using pregnancy, labor, intervention-related features...

Abstract Introduction Conflicting results persist regarding the effectiveness of robotic-assisted gait training (RAGT) for functional recovery in post-stroke survivors. We used several machine learning algorithms to construct prediction models outcomes robotic neurorehabilitation adult patients. Methods and materials Data 139 patients who underwent Lokomat at Taipei Medical University Hospital were retrospectively collected. After screening data completeness, records 91 with acute or chronic...

Abstract Background Due to the spread of coronavirus disease 2019 (COVID-19) pandemic in 2020, interest nutritional supplements has emerged. Limited data are available on how COVID-19 affects search Taiwan and worldwide. The study aims investigate changes public pre- during pandemic. Methods Our World Data dataset was used collect both global local (Taiwan) number newly confirmed cases deaths. Google Trends query being obtain relative volumes (RSVs) covering a timeframe between 2022....

This study aimed to investigate the possible incidence of visual light perceptions (VLPs) during radiation therapy (RT). We analyzed whether VLPs could be affected by differences in energy, prescription doses, age, sex, or RT locations, and all were caused radiation. From November 2016 August 2018, a total 101 patients who underwent head-and-neck brain screened. After receiving RT, questionnaires completed, subjects interviewed. Random forests (RF), tree-based machine learning algorithm,...

Acknowledging the extreme risk COVID-19 poses to humans, this paper attempted analyze and compare case fatality rates, identify existence of learning curves for medical treatments, examine impact vaccination on rate reduction. Confirmed cases deaths were extracted from "Daily Situation Report" provided by World Health Organization. The results showed that low registration viral test rates resulted in curve was significant all countries except China. Treatment can be improved through repeated...

<sec> <title>BACKGROUND</title> Predictions in pregnancy care are complex because of interactions among multiple factors. Hence, outcomes not easily predicted by a single predictor using only one algorithm or modeling method. </sec> <title>OBJECTIVE</title> This study aims to review and compare the predictive performances between logistic regression (LR) other machine learning algorithms for developing validating multivariable prognostic prediction model inform clinicians’ decision making....

Background The International Classification of Functioning, Disability and Health (ICF) core set (CS) facilitates the standardization functioning impairment assessment for integration holistic care. Objective This study developed an ICF CS interviewing pediatric brain tumor survivors in Taiwan to help healthcare professionals implementing disability management measures. Methods A group 29 experts 10 relevant fields with at least 5 years experience working children tumors participated this...