Decision tree

pH-mediated drug-drug interactions (DDI) is a prevalent DDI in drug development, especially for weak base compounds with highly pH-dependent solubility. FDA has released a guidance on the evaluation of pH-mediated DDI assessments using in vitro testing and clinical studies. Currently, there is no common practice of ways of testing across the academia and industry. The development of biopredictive method and physiologically-based biopharmaceutics modeling (PBBM) approaches to assess acid-reducing agent (ARA)-DDI have been proven with accurate prediction and could decrease drug development burden, inform clinical design and potentially waive clinical studies...

Electroencephalogram (EEG) provides noninvasive measures of brain activity and is found to be valuable for the diagnosis of some chronic disorders. Specifically, pre-treatment EEG signals in the alpha and theta frequency bands have demonstrated some association with antidepressant response, which is well-known to have a low response rate. We aim to design an integrated pipeline that improves the response rate of patients with major depressive disorder by developing a treatment policy guided by the resting state pre-treatment EEG recordings and other treatment effects modifiers...

INTRODUCTION: Common Temporomandibular Disorders (TMD) involve the masticatory muscles, temporomandibular joints, and/or their associated structures. Clinical manifestations can vary, including sounds (cracking, crepitus), pain, and/or dyskinesias, often corresponding to a limitation of mandibular movements. Signs or symptoms of muscular or joint disorders of the masticatory system may be present before the initiation of orthodontic treatment, emerge during treatment, or worsen to the point of stopping treatment...

Mild cognitive impairment (MCI) is a neuropsychological syndrome that is characterized by cognitive impairments. It typically affects adults 60 years of age and older. It is a noticeable decline in the cognitive function of the patient, and if left untreated it gets converted to Alzheimer's disease (AD). For that reason, early diagnosis of MCI is important as it slows down the conversion of the disease to AD. Early and accurate diagnosis of MCI requires recognition of the clinical characteristics of the disease, extensive testing, and long-term observations...

BACKGROUND: Human albumin (HA) is an effective adjuvant treatment for patients with cirrhosis developing spontaneous bacterial peritonitis (SBP), hepatorenal syndrome (HRS) and ascites requiring large-volume paracentesis (LVP). However, cost remains a barrier to use, particularly in resource-limited settings. This study aims to assess the cost-effectiveness of HA in patients with cirrhosis with SBP, HRS or ascites requiring LVP in the Indonesian healthcare system as a representative of a resource-limited setting...

Artificial intelligence is steadily permeating various sectors, including healthcare. This research specifically addresses lung cancer, the world's deadliest disease with the highest mortality rate. Two primary factors contribute to its onset: genetic predisposition and environmental factors, such as smoking and exposure to pollutants. Recognizing the need for more effective diagnosis techniques, our study embarked on devising a machine learning strategy tailored to boost precision in lung cancer detection...

Nonalcoholic fatty liver disease (NAFLD) has emerged as the predominant chronic liver condition globally, and underdiagnosis is common, particularly in mild cases, attributed to the asymptomatic nature and traditional ultrasonography's limited sensitivity to detect early-stage steatosis. Consequently, patients may experience progressive liver pathology. The objective of this research is to ascertain the efficacy of serum glycan glycopatterns as a potential diagnostic biomarker, with a particular focus on the disease's early stages...

After stroke rehabilitation, patients need to reintegrate back into their daily life, workplace and society. Reintegration involves complex processes depending on age, sex, stroke severity, cognitive, physical, as well as socioeconomic factors that impact long-term outcomes post-stroke. Moreover, post-stroke quality of life can be impacted by social risks of inadequate family, social, economic, housing and other supports needed by the patients. Social risks and barriers to successful reintegration are poorly understood yet critical for informing clinical or social interventions...

BACKGROUND: Postoperative ileus (POI) continues to be a major cause of morbidity following colorectal surgery. Despite best efforts, the incidence of POI in colorectal surgery remains high (~30%). This study aimed to investigate machine learning techniques to identify risk factors for POI in colorectal surgery patients, to help guide further preventative strategies. METHODS: A TRIPOD-guideline-compliant retrospective study was conducted for major colorectal surgery patients at a single tertial care centre (2018-2022)...

BACKGROUND: EPs pose significant challenges to individual health and quality of life, attracting attention in public health as a risk factor for diminished quality of life and healthy life expectancy in middle-aged and older adult populations. Therefore, in the context of global aging, meticulous exploration of the factors behind emotional issues becomes paramount. Whether ADL can serve as a potential marker for EPs remains unclear. This study aims to provide new evidence for ADL as an early predictor of EPs through statistical analysis and validation using machine learning algorithms...

Climate change is predicted to disproportionately impact sub-Saharan Africa, with potential devastating consequences on plant populations. Climate change may, however, impact intraspecific taxa differently. The aim of the study was to determine the current distribution and impact of climate change on three varieties of Vachellia sieberiana , that is, var. sieberiana , var. villosa and var. woodii . Ensemble species distribution models (SDMs) were built in "biomod2" using 66, 45, and 137 occurrence records for var...

Due to the importance of accurate diagnosis and prompt treatment of this condition, the medical world is searching for a solution for its early detection and efficient treatment. Heart disease is one of the leading causes of death in modern society. With the development of computer science today, this issue can be resolved using computers. Data mining is one of the solutions for diagnosing this illness. One of the cutting-edge disciplines, data mining, can aid in better decision-making in many areas of medicine, including disease diagnosis and treatment...

BACKGROUND: Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with comprehensive health-related characteristics, and used machine learning (ML) to construct diagnostic models of cognitive impairment (CI). METHODS: The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, and we recruited 823 participants aged 65 years and older, who completed a comprehensive health assessment and cognitive function assessments...

BACKGROUND/OBJECTIVES: No simple, accurate diagnostic tests exist for exocrine pancreatic insufficiency (EPI), and EPI remains underdiagnosed in chronic pancreatitis (CP). We sought to develop a digital screening tool to assist clinicians to predict EPI in patients with definite CP. METHODS: This was a retrospective case-control study of patients with definite CP with/without EPI. Overall, 49 candidate predictor variables were utilized to train a Classification and Regression Tree (CART) model to rank all predictors and select a parsimonious set of predictors for EPI status...

INTRODUCTION: A prototype lateral flow device detecting cytokine biomarkers interleukin (IL)-1α and IL-1β has been developed as a point-of-care test-called the Genital InFlammation Test (GIFT)-for detecting genital inflammation associated with sexually transmitted infections (STIs) and/or bacterial vaginosis (BV) in women. In this paper, we describe the rationale and design for studies that will be conducted in South Africa, Zimbabwe and Madagascar to evaluate the performance of GIFT and how it could be integrated into routine care...

Compared to typical anaerobic digestion processes, little is known about both sludge microbial compositions and biogas production models for full-scale dry methane fermentation treating municipal solid waste (MSW). The anaerobic sludge composed of one major hydrogenotrophic methanogen (Methanoculleus) and syntrophic acetate oxidizing bacteria (e.g., Caldicoprobacter), besides enrichment of MSW degraders such as Clostridia. The core population remained phylogenetically unchanged during the fermentation process, regardless of amounts of MSW supplied (∼35 ton/d) or biogas produced (∼12000 Nm3 /d)...

OBJECTIVE: Chordomas are rare tumors of the skull base and spine believed to arise from the vestiges of the embryonic notochord. These tumors are locally aggressive and frequently recur following resection and adjuvant radiotherapy. Proton therapy has been introduced as a tissue-sparing option because of the higher level of precision that proton-beam techniques offer compared with traditional photon radiotherapy. This study aimed to compare recurrence in patients with chordomas receiving proton versus photon radiotherapy following resection by applying tree-based machine learning models...

The expansion of cocoa farms is a major driver of deforestation and emissions in Ghana's high forest zone. The Ghana Cocoa Forest Reducing Emissions from Deforestation and Forest Degradation Program (REDD+) was launched as the world's first commodity-based initiative to address emissions from deforestation caused by cocoa production and generate non-carbon benefits. Hotspot Intervention Areas were established to implement the Ghana Cocoa REDD+ program. This study combines Q-methodology with focus group discussions and interviews to assess stakeholder perceptions in the Juabuso-Bia cocoa landscape regarding the capacity of the Hotspot Intervention Area to facilitate the generation of governance and economic non-carbon benefits to sustain emission reductions...

OBJECTIVES: Clinical prediction rules are used to discriminate patients with locomotive syndrome and may enable early detection. This study aimed to validate the clinical predictive rules for locomotive syndrome in community-dwelling older adults. METHODS: We assessed the clinical prediction rules for locomotive syndrome in a cross-sectional setting. The age, sex, and body mass index of participants were recorded. Five physical function tests-grip strength, single-leg standing time, timed up-and-go test, and preferred and maximum walking speeds-were measured as predictive factors...

OBJECTIVES: Accurately predicting the likelihood of inpatients' home discharge in a convalescent ward is crucial for assisting patients and families in decision-making. While logistic regression analysis has been commonly used, its complexity limits practicality in clinical settings. We focused on decision tree analysis, which is visually straightforward. This study aimed to develop and validate the accuracy of a prediction model for home discharge for inpatients in a convalescent ward using a decision tree analysis...