We demonstrate the potential of machine learning to gather, track, and analyze symptoms experienced by cancer patients during chemotherapy. Although our initial model requires further optimization to improve the performance, further model building may yield machine learning methods suitable to be deployed in routine clinical care, quality improvement, and research applications.
A 62-year-old woman presented with breathlessness and dysphagia. Routine chest x-ray showed a widening in the upper mediastinum that suggested a thoracic aorta enlargement. No cardiomegaly was found (A). Transthoracic echocardiography revealed normal left ventricular systolic function with diastolic dysfunction and aortic sclerosis. Magnetic resonance angiography demonstrated a double aortic arch forming a vascular ring, thus compressing the esophagus (B to D). This is a rare congenital cardiovascular disorder (1%), usually diagnosed at an early age. It is possible to reach middle to late adulthood with this pathology, as shown by this patient, and it can produce severe symptoms by compressing the trachea and esophagus. AA ϭ ascending aorta; E ϭ esophagus; LCCA ϭ left common carotid artery; LSA ϭ left subclavian artery; PA ϭ pulmonary artery; RCCA ϭ right common carotid artery; RSA ϭ right subclavian artery; T ϭ trachea.
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