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Dyspnea is a frequent symptom resulting from multiple pathological attacks. Indeed, this

symptom can have a cardiac, pulmonary, metabolic, psychological or muscular origin. In this context, a multimodal approach is required in order to identify the determining factor in the approach of this symptom which can be a source of overconsumption of additional examinations and diagnostic errors.

The dyspnea approach is classically described as a stopgap but can sometimes be explored by various approaches depending on the suspected diagnostic orientation. The patient sometimes benefits from a biological assessment in first intension where others will meet an organ specialist (cardiologist, pulmonologist, …) or even will carry out a thoracic scan as a first-line.

The potentiation of the examinations through an automated analysis of the data could make it possible to quickly guide towards a reliable diagnosis but also an adapted treatment. In addition, an exhaustive analysis of the data would potentiate the impact of the various examinations in terms of screening (e.g. osteoporosis in thoracic imaging or mammary neoplasia or coronary artery disease) while the diagnostic question focuses the study on the objective of the examination.

Revolutionizing Dyspnea Diagnosis: A Multimodal, Data-Driven Approach for Accurate and Efficient Care

Dyspnea’s diverse causes demand a multimodal diagnostic approach. Automated data analysis can streamline accurate diagnosis, improving screening and patient care efficiency.

ClientCHU de Liège (university Hospital)Year2021AuthorPeter Van KerkhoveShare

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