AIMC Topic: Internet

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Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease.

Italian journal of pediatrics
BACKGROUND: Kawasaki disease (KD) is a leading cause of acquired heart disease in children that is treated with intravenous immunoglobulin (IVIG). However, 10-20% of cases exhibit IVIG resistance, which increases the risk of coronary complications. E...

It's raining bots: how easier access to internet surveys has created the perfect storm.

BMJ open quality
Online surveys are an increasingly common way to collect data from the public, with social media and financial incentives (e.g. gift cards) commonly used to increase participation rates. Anonymity, ease of response, and the potential to reach diverse...

Clinical, genetic, and sociodemographic predictors of symptom severity after internet-delivered cognitive behavioural therapy for depression and anxiety.

BMC psychiatry
BACKGROUND: Internet-delivered cognitive behavioural therapy (ICBT) is an effective and accessible treatment for mild to moderate depression and anxiety disorders. However, up to 50% of patients do not achieve sufficient symptom relief. Identifying p...

Temporal user interest modeling for online advertising using Bi-LSTM network improved by an updated version of Parrot Optimizer.

Scientific reports
In the era of digitization, online digital advertising is one of the best techniques for modern marketing. This makes advertisers rely heavily on accurate user interest and behavior modelling to deliver precise advertisement impressions and increase ...

Ambivalent User Needs as a Challenge and Chance for the Design of a Web-Based Intervention for Gaming Disorder: Qualitative Interview Study With Adolescents and Young Adults.

JMIR formative research
BACKGROUND: In Germany, there are still many young people with gaming disorder (GD) who do not use or cannot access existing treatment services. Given the increasing prevalence of internet use disorders and GD, especially among young people in German...

Co-designing an online educational resource to help adolescents improve their digital health literacy.

BMC public health
BACKGROUND: Digital media is ubiquitous in adolescents' lives and provides many opportunities to engage with health information. However, there is an increased risk of engaging with inaccurate or biased health information on the internet, resulting i...

Intelligent predictive risk assessment and management of sarcopenia in chronic disease patients using machine learning and a web-based tool.

European journal of medical research
BACKGROUND: Individuals with chronic diseases are at higher risk of sarcopenia, and precise prediction is essential for its prevention. This study aims to develop a risk scoring model using longitudinal data to predict the probability of sarcopenia i...

Machine learning approach for optimizing usability of healthcare websites.

Scientific reports
In today's digital era, hospital websites serve as crucial informational resources, providing patients with easy access to medical services. Ensuring the usability of these websites is essential, as it directly impacts users' ability to navigate and ...

Deep learning modelling to forecast emergency department visits using calendar, meteorological, internet search data and stock market price.

Computer methods and programs in biomedicine
BACKGROUND: Accurate prediction of hospital emergency department (ED) patient visits and acuity levels have potential to improve resource allocation including manpower planning and hospital bed allocation. Internet search data have been used in medic...

Preoperative lymph node metastasis risk assessment in invasive micropapillary carcinoma of the breast: development of a machine learning-based predictive model with a web-based calculator.

World journal of surgical oncology
BACKGROUND: Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer characterized by a high risk of lymph node metastasis (LNM). The study aimed to identify predictors of LNM and to develop a machine learning (ML)-based risk predi...