Publications by authors named "Alejandro Renato"

In this work we document the development of an ASR system for the transcription of conversations between patient and doctor and we will point out the critical aspects of the domain. The system was trained with an acoustic base of spontaneous speech that has a domain language model and a supervised phonetic dictionary. Its performance was compared with two systems: a) NeMo End-to-End Conformers in Spanish and b) Google API ASR (Automatic Speech Recognition) Cloud.

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Creating notes in the EHR is one of the most problematic aspects for health professionals. The main challenges are the time spent on this task and the quality of the records. Automatic speech recognition technologies aim to facilitate clinical documentation for users, optimizing their workflow.

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Introduction: Hypertension is the main cause of cognitive impairment and the executive dysfunction the most com- mon cognitive domain affected. The aims of this research have been to characterize the cognitive profiles (s) in hypertensive patients and to identify the most usefulness Test (s) in the routine clinical practice to identify them.

Methods: We assessed the cognitive status in 69 hypertensive patients who were administered a battery of cognitive Tests that included the MMSE, the Mini-Boston Naming Test, verbal fluency and the Clock drawing Test.

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The COVID-19 social isolation period entailed changes in daily habits and routines, testing the adjustment abilities of the population to address unusual situations. Given that the activities of daily living require a normally functioning cognitive system, the study of cognitive-functional interaction under social isolation is relevant. The object of this work was to obtain information on the cognitive-functional impact of social isolation, analyze the changes induced in daily routines and habits, and assess the cognitive adjustment of the adult population to the isolation requirements.

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Clinical documentation in healthcare institutions is one of the daily tasks that consumes most of the time for those involved. The adoption of mobile devices in medical practice increases efficiency among healthcare professionals. We describe the design and evaluation of an automatic speech recognition system that enables the transcription of audio to text of clinical notes in a mobile environment.

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Background: The Memory Impairment Screen (MIS-A) is a validated test to detect Alzheimer's Disease (AD) and other dementias. We have modified this test to suit a Spanish speaking population and added a new component, delayed recall (MIS-D).

Objectives: 1) To test a Spanish version of MIS-A and MIS-D.

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