Publicación

Depression Detection Using Audio-Visual Data and Artificial Intelligence: A Systematic Mapping Study

José Balbuena · Hilda Samamé · Silvana Almeyda · Juan Alonso Tello Mendoza · José Antonio Pow-Sang
2020 Advances in intelligent systems and computing DOI: 10.1007/978-981-15-5859-7_29

Resumen

Major depression disorder is a mental issue that has been increasing in the last decade, in consequence, prediction or detection of this mental disorder in early stages is necessary. Artificial intelligence techniques have been developed in order to ease the diagnosis of different illnesses, including depression, using audio-visual information such as voice or video recordings and medical images. This research field is growing, and some organizations and descriptions are required. In the present work, a systematic mapping study was conducted in order to summarize the factors involved in depression detection such as artificial intelligence techniques, source of information, and depression scales.

Autores y colaboradores

Authors

José Balbuena
Hilda Samamé
Silvana Almeyda
Juan Alonso Tello Mendoza
José Antonio Pow-Sang

Palabras clave

Artificial intelligence Deep learning Depression detection Machine learning Systematic mapping study Video Voice