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End Users' Perception on an AI Chatbot in a Snus Cessation Mobile Application.

Studies in health technology and informatics
This study examines end-user perceptions of an AI chatbot as a virtual therapist through a design study of ExSnus, a prototype of a mobile health application designed to assist users in quitting snus. ExSnus includes features such as a forum to share...

Chronic Pain Prevalence, Opioid Use, and Primary Care Provider Opioid Prescription Patterns in the U.S. from 2017 to 2019 Derived from Medicaid Claims Data.

Studies in health technology and informatics
Chronic non-cancer pain (CNCP) is a major health concern in the United States, incurring substantial healthcare costs and frequently requiring opioid therapy in primary care. This retrospective cross-sectional study used Medicaid claims data from six...

Early Identification of Vitamin D Deficiency Risk Through Public Health Screening Data.

Studies in health technology and informatics
Metabolic syndrome, characterized by central obesity, hypertension, hyperglycemia, dyslipidemia, and reduced high-density lipoprotein levels, significantly increases the risk of cardiovascular diseases. Vitamin D, essential for calcium regulation and...

Algorithmic Fairness in Machine Learning Prediction of Autism Using Electronic Health Records.

Studies in health technology and informatics
Efforts to improve early diagnosis of autism spectrum disorder (ASD) in children are beginning to use machine learning (ML) approaches applied to real-world clinical datasets, such as electronic health records (EHRs). However, sex-based disparities i...

Personalized Prediction of Chronic Kidney Disease Progression in Patients with Chronic Kidney Disease Stages 3-5: A Multicenter Study Using the Machine Learning Approach.

Studies in health technology and informatics
Chronic Kidney Disease (CKD) is a prevalent and progressive condition that can lead to end-stage renal disease (ESRD) if left unmanaged. Accurate prediction of CKD progression, particularly in patients with CKD stages 3-5, is essential for early inte...

Early Detection of Acute Coronary Syndrome Using a Mobile Digital Health Application.

Studies in health technology and informatics
Early detection of acute coronary syndrome (ACS) is vital for reducing ischemic time and preserving more heart muscle.Chest pain is the most common symptom of acute coronary syndrome (ACS). This study used a quick chest pain assessment questionnaire ...

ICU Length of Stay Prediction for Patients with Diabetes Using Machine Learning and Clinical Notes.

Studies in health technology and informatics
Diabetes, a chronic disease, often leads to poor health outcomes and increased healthcare costs, particularly for patients admitted to ICU. Accurate early prediction of ICU length of stay (LOS) is vital for hospital resource management and patient ou...

Enhancing Chronic Diabetes Care with Companion Robots in Rural Taiwan.

Studies in health technology and informatics
Managing chronic diabetes in rural Taiwan remains challenging due to limited medical access and low health literacy. This pilot study evaluated a two-month, two-phase intervention using Bluetooth-enabled glucometers, smart wristbands, and a gamified ...

Type 2 Diabetes Subtyping via Phenotype and Genotype Co-Learning.

Studies in health technology and informatics
Interpreting and subtyping type 2 diabetes (T2D) is challenging yet essential for achieving fine-grained pathophysiological insights and precise clinical stratification. Previous studies have primarily relied on a small number of pre-selected risk fa...

Accuracy of Large Language Models in Generating Rare Disease Differential Diagnosis Using Key Clinical Features.

Studies in health technology and informatics
Generating differential diagnoses for rare disease patients can be time intensive and highly dependent on the background and training of the evaluating physicians. Large language models (LLMs) have the potential to complement this process by automati...