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Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden.

International journal of medical informatics
OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (eCOPD), or pneumonia, which are often misdiagnosed. We aimed to create...

Biomechanical analysis on neurotypical and autism spectrum disorder people during human-cobot interaction.

Applied ergonomics
Biomechanical analysis is essential for assessing subjects interacting with robotic setups and platforms. However, in industrial scenarios, workers' biomechanics are assessed mainly through questionnaires and scales which provide limited objectivity....

Evaluation of insulin sensitivity temporal prediction by using quantile regression combined with neural network model.

International journal of medical informatics
BACKGROUND: Stress-induced hyperglycemia, a pathologically high blood glucose level, is a frequent complication in intensive care units. Blood glucose (BG) level control is crucial but challenging due to patient variability. The Stochastic TARgeted (...

Comparison of CT referral justification using clinical decision support and large language models in a large European cohort.

European radiology
BACKGROUND: Ensuring appropriate use of CT scans is critical for patient safety and resource optimization. Decision support tools and artificial intelligence (AI), such as large language models (LLMs), have the potential to improve CT referral justif...

Deep Learning-Augmented Sleep Spindle Detection for Acute Disorders of Consciousness: Integrating CNN and Decision Tree Validation.

IEEE transactions on bio-medical engineering
Sleep spindles, which are key biomarkers of non-rapid eye movement stage 2 sleep, play a crucial role in predicting outcomes for patients with acute disorders of consciousness (ADOC). However, several critical challenges remain in spindle detection: ...

Multi-View Self-Supervised Learning Enhances Automatic Sleep Staging From EEG Signals.

IEEE transactions on bio-medical engineering
Deep learning-based methods for automatic sleep staging offer an efficient and objective alternative to costly manual scoring. However, their reliance on extensive labeled datasets and the challenge of generalization to new subjects and datasets limi...

An Active Insole to Reduce Plantar Pressure Loading: Using Predictive Finite Element Driven Soft Hydraulic Actuators to Minimize Plantar Pressure and the Pressure Time Integral for Diabetic Foot Ulceration Risk Management.

IEEE transactions on bio-medical engineering
OBJECTIVE: This article aims to design, manufacture and evaluate an active insole to reduce plantar tissue loading to minimise the risk of diabetic foot ulceration for people living with diabetes.

Why is AI Not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling.

IEEE transactions on visualization and computer graphics
This paper explores the potential for human-AI collaboration in the context of data storytelling for data workers. Data storytelling communicates insights and knowledge from data analysis. It plays a vital role in data workers' daily jobs since it bo...

Analysis and characterization of extrachromosomal circular DNA in prostate cancer: Potential biomarker discovery from urine, plasma, and tumor samples.

Cancer letters
Extrachromosomal circular DNA (eccDNA) may contribute to genomic rearrangements and tumor heterogeneity, playing a role in cancer development and progression. This study evaluates eccDNA as a biomarker for prostate cancer by characterizing its profil...

Machine learning algorithms with body fluid parameters: an interpretable framework for malignant cell screening in cerebrospinal fluid.

Clinical chemistry and laboratory medicine
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model utilizing cerebrospinal fluid (CSF) body fluid parameters from hematology analyzers to screen for malignant cells.