AIMC Topic: Netherlands

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Gut microbiota shift in Ghanaian individuals along the migration axis: the RODAM-Pros cohort.

Gut microbes
Migration is associated with a substantial change in environmental exposures and health outcomes. We aimed to investigate the shift in gut microbiota composition and the associations with cardiometabolic outcomes in the RODAM-Pros cohort spanning mul...

Predicting quality of life of patients after treatment for spinal metastatic disease: development and internal evaluation.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: When treating spinal metastases in a palliative setting, maintaining or enhancing quality of life (QoL) is the primary therapeutic objective. Clinicians tailor their treatment strategy by weighing the QoL benefits against expected...

Diagnosis extraction from unstructured Dutch echocardiogram reports using span- and document-level characteristic classification.

BMC medical informatics and decision making
BACKGROUND: Clinical machine learning research and artificial intelligence driven clinical decision support models rely on clinically accurate labels. Manually extracting these labels with the help of clinical specialists is often time-consuming and ...

Machine-learning based prediction of appendicitis for patients presenting with acute abdominal pain at the emergency department.

World journal of emergency surgery : WJES
BACKGROUND: Acute abdominal pain (AAP) constitutes 5-10% of all emergency department (ED) visits, with appendicitis being a prevalent AAP etiology often necessitating surgical intervention. The variability in AAP symptoms and causes, combined with th...

Report of the First ONTOX Hackathon: Hack to Save Lives and Avoid Animal Suffering. The Use of Artificial Intelligence in Toxicology - A Potential Driver for Reducing/Replacing Laboratory Animals in the Future.

Alternatives to laboratory animals : ATLA
The first ONTOX Hackathon of the EU Horizon 2020-funded ONTOX project was held on 21-23 April 2024 in Utrecht, The Netherlands (https://ontox-project.eu/hackathon/). This participatory event aimed to collectively advance innovation for human safety t...

Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection.

BMC medical informatics and decision making
BACKGROUND: Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the Intensive Care Unit (ICU). Timely and accurate identification of BT needs can enhance patient outcomes and healthcare resource management.

Examining the Meaning of "Violence" Through Machine Learning Techniques.

Journal of interpersonal violence
This paper examines the meaning of violence in contemporary Western societies. Scholars have argued that in contemporary Western societies, the concept is expanding toward a broader understanding of violence, beyond its "traditional" usage in the con...

Effect of a Machine Learning-Derived Early Warning Tool With Treatment Protocol on Hypotension During Cardiac Surgery and ICU Stay: The Hypotension Prediction 2 (HYPE-2) Randomized Clinical Trial.

Critical care medicine
OBJECTIVES: Cardiac surgery is associated with perioperative complications, some of which might be attributable to hypotension. The Hypotension Prediction Index (HPI), a machine-learning-derived early warning tool for hypotension, has only been evalu...

Keeping pace in the age of innovation: The perspective of Dutch pharmaceutical science students on the position of machine learning training in an undergraduate curriculum.

Currents in pharmacy teaching & learning
BACKGROUND: Over the years, approaches of the pharmaceutical industry to discover and develop drugs have changed rapidly due to new scientific trends. Among others, they have started to explore Machine Learning (ML), a subset of Artificial Intelligen...

Bias Sensitivity in Diagnostic Decision-Making: Comparing ChatGPT with Residents.

Journal of general internal medicine
BACKGROUND: Diagnostic errors, often due to biases in clinical reasoning, significantly affect patient care. While artificial intelligence chatbots like ChatGPT could help mitigate such biases, their potential susceptibility to biases is unknown.