From the review of the research articles analyzed, it can be said that use of social robots in elderly people without cognitive impairment and with dementia, help in a positive way to work independently in basic activities and mobility, provide security, and reduce stress.

Data Mining in medicine is an emerging field of great importance to provide a prognosis and deeper understanding of disease classification, specifically in Mental Health areas. The main objective of this paper is to present a review of the existing research works in the literature, referring to the techniques and algorithms of Data Mining in Mental Health, specifically in the most prevalent diseases such as: Dementia, Alzheimer, Schizophrenia and Depression. Academic databases that were used to perform the searches are Google Scholar, IEEE Xplore, PubMed, Science Direct, Scopus and Web of Science, taking into account as date of publication the last 10 years, from 2008 to the present. Several search criteria were established such as 'techniques' AND 'Data Mining' AND 'Mental Health', 'algorithms' AND 'Data Mining' AND 'dementia' AND 'schizophrenia' AND 'depression', etc. selecting the papers of greatest interest. A total of 211 articles were found related to techniques and algorithms of Data Mining applied to the main Mental Health diseases. 72 articles have been identified as relevant works of which 32% are Alzheimer's, 22% dementia, 24% depression, 14% schizophrenia and 8% bipolar disorders. Many of the papers show the prediction of risk factors in these diseases. From the review of the research articles analyzed, it can be said that use of Data Mining techniques applied to diseases such as dementia, schizophrenia, depression, etc. can be of great help to the clinical decision, diagnosis prediction and improve the patient's quality of life.

Suicide is the second cause of death in young people. The use of technologies as tools facilitates the detection of individuals at risk of suicide thus allowing early intervention and efficacy. Suicide can be prevented in many cases. Technology can help people at risk of suicide and their families. It could prevent situations of risk of suicide with the technological evolution that is increasing. This work is a systematic review of research papers published in the last ten years on technology for suicide prevention. In September 2017, the consultation was carried out in the scientific databases PubMed, ScienceDirect, PsycINFO, The Cochrane Library and Google Scholar. A general search was conducted with the terms "prevention" AND "suicide" AND "technology. More specific searches included technologies such as "Web", "mobile", "social networks", and others terms related to technologies. The number of articles found following the methodology proposed was 90, but only 30 are focused on the objective of this work. Most of them were Web technologies (51.61%), mobile solutions (22.58%), social networks (12.90%), machine learning (3.23%) and other technologies (9.68%). According to the results obtained, although there are technological solutions that help the prevention of suicide, much remains to be done in this field. Collaboration among technologists, psychiatrists, patients, and family members is key to advancing the development of new technology-based solutions that can help save lives.

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