AIMC Topic: Switzerland
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Reducing food waste in the HORECA sector using AI-based waste-tracking devices.
Waste management (New York, N.Y.)
Mar 1, 2025
This study assesses the effectiveness of an intervention employing an AI-based, fully automatic waste-tracking system for food waste reduction in HORECA establishments. Waste-tracking devices were installed in a restaurant within a holiday resort and...
Exploring correlates of high psychiatric inpatient utilization in Switzerland: a descriptive and machine learning analysis.
BMC psychiatry
Dec 23, 2024
BACKGROUND: This study investigated socio-demographic, psychiatric, and psychological characteristics of patients with high versus low utilization of psychiatric inpatient services. Our objective was to better understand the utilization pattern and t...
Spatiotemporal modelling of airborne birch and grass pollen concentration across Switzerland: A comparison of statistical, machine learning and ensemble methods.
Environmental research
Sep 20, 2024
BACKGROUND: Statistical and machine learning models are commonly used to estimate spatial and temporal variability in exposure to environmental stressors, supporting epidemiological studies. We aimed to compare the performances, strengths and limitat...
Perspectives of medical imaging professionals about the impact of AI on Swiss radiographers.
Journal of medical imaging and radiation sciences
Aug 27, 2024
INTRODUCTION: Artificial Intelligence (AI) is increasingly implemented in medical imaging practice, however, its impact on radiographers practice is not well studied. The aim of this study was to explore the perceived impact of AI on radiographers' a...
Attitude of aspiring orthopaedic surgeons towards artificial intelligence: a multinational cross-sectional survey study.
Archives of orthopaedic and trauma surgery
Aug 10, 2024
INTRODUCTION: The purpose of this study was to evaluate the perspectives of aspiring orthopaedic surgeons on artificial intelligence (AI), analysing how gender, AI knowledge, and technical inclination influence views on AI. Additionally, the extent t...
Shaping future practices: German-speaking medical and dental students' perceptions of artificial intelligence in healthcare.
BMC medical education
Aug 6, 2024
BACKGROUND: The growing use of artificial intelligence (AI) in healthcare necessitates understanding the perspectives of future practitioners. This study investigated the perceptions of German-speaking medical and dental students regarding the role o...
Developing and testing a framework for coding general practitioners' free-text diagnoses in electronic medical records - a reliability study for generating training data in natural language processing.
BMC primary care
Jul 16, 2024
BACKGROUND: Diagnoses entered by general practitioners into electronic medical records have great potential for research and practice, but unfortunately, diagnoses are often in uncoded format, making them of little use. Natural language processing (N...
No playing around with robots? Ambivalent attitudes toward the use of Paro in elder care.
Nursing inquiry
May 29, 2024
This paper explores the ways in which health care professionals, family carers, and older persons expressed attitudes and opinions on using Paro, a social robot designed to stimulate patients with dementia. Thereafter, we critically evaluate existing...
Multispecies deep learning using citizen science data produces more informative plant community models.
Nature communications
May 24, 2024
In the age of big data, scientific progress is fundamentally limited by our capacity to extract critical information. Here, we map fine-grained spatiotemporal distributions for thousands of species, using deep neural networks (DNNs) and ubiquitous ci...
Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.
Surgical endoscopy
May 22, 2024
BACKGROUND: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study evaluates the feasibility of predicting AL using machine learning (ML) algorithms based on preoperative ...
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