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The transmission through contacts among MSM (men who have sex with men) is one of the dominating contributors to HIV prevalence in industrialized countries. In Amsterdam, the capital of the Netherlands, the MSM risk group has been traced…
Machine Learning Health Operations (MLHOps) is the combination of processes for reliable, efficient, usable, and ethical deployment and maintenance of machine learning models in healthcare settings. This paper provides both a survey of work…
Over the past decade, the use of machine learning (ML) models in healthcare applications has rapidly increased. Despite high performance, modern ML models do not always capture patterns the end user requires. For example, a model may…
Online learning and MOOCs have become increasingly popular in recent years, and the trend will continue, given the technology boom. There is a dire need to observe learners' behavior in these online courses, similar to what instructors do…
Scientific publications about machine learning in healthcare are often about implementing novel methods and boosting the performance - at least from a computer science perspective. However, beyond such often short-lived improvements, much…
Rough sleeping is a chronic problem faced by some of the most disadvantaged people in modern society. This paper describes work carried out in partnership with Homeless Link, a UK-based charity, in developing a data-driven approach to…
Recently the patient centered medical home (PCMH) model has become a popular approach to deliver better care to patients. Current research shows that the most important key for succession of this method is to make balance between healthcare…
Access to combination antiretroviral treatment (ART) has improved greatly over recent years. At the end of 2011, more than eight million HIV infected people were receiving antiretroviral therapy in low-income and middle-income countries.…
When a deep learning model is trained sequentially on different datasets, it often forgets the knowledge learned from previous data, a problem known as catastrophic forgetting. This damages the model's performance on diverse datasets, which…
Given a collection of features available for inclusion in a predictive model, it may be of interest to quantify the relative importance of a subset of features for the prediction task at hand. For example, in HIV vaccine trials, participant…
Repetitive laboratory testing unlikely to yield clinically useful information is a common practice that burdens patients and increases healthcare costs. Education and feedback interventions have limited success, while general test ordering…
Sexual contacts are the main spreading route of HIV. This puts sex workers at higher risk of infection even in populations where HIV prevalence is moderate or low. Alongside condom use, Pre-Exposure Prophylaxis (PrEP) is an effective tool…
Hypertension is a major risk factor for stroke, cardiovascular disease, and end-stage renal disease, and its prevalence is expected to rise dramatically. Effective hypertension management is thus critical. A particular priority is…
Homelessness among US veterans remains a critical public health challenge, yet risk prediction offers a pathway for proactive intervention. In this retrospective prognostic study, we analyzed electronic health record (EHR) data from…
Immune interventions consisting in repeated injection are broadly used as they are thought to improve the quantity and the quality of the immune response. However, they also raised several questions that remains unanswered, in particular…
Heart failure (HF) is a leading cause of morbidity, mortality, and health care costs. Prolonged conduction through the myocardium can occur with HF, and a device-driven approach, termed cardiac resynchronization therapy (CRT), can improve…
Social context plays an important role in perpetuating or reducing HIV risk behaviors. This study analyzed the network and individual attributes that were associated with the likelihood that people who inject drugs (PWID) will engage in HIV…
The inherent complexity of structured longitudinal Electronic Health Records (EHR) data poses a significant challenge when integrated with Large Language Models (LLMs), which are traditionally tailored for natural language processing.…
The Population-based HIV Impact Assessment (PHIA) is an ongoing project that conducts nationally representative HIV-focused surveys for measuring national and regional progress toward UNAIDS' 90-90-90 targets, the primary strategy to end…
Background. Real-world data show that approximately 50% of psoriasis patients treated with a biologic agent will discontinue the drug because of loss of efficacy. History of previous therapy with another biologic, female sex and obesity…