RESEARCH

ALENTAR-J-CM Project

ALENTAR-J-CM is a research project that uses Artificial Intelligence (AI) and Large Language Models (LLMs) to early detection and prevention the risk of emotional disorders and suicide in young people.

Learn about ALENTAR

RESEARCH

ALENTAR-J-CM
Project

Learn about ALENTAR

Research partners

Collaborating partners

ABOUT ALENTAR-J-CM

The story behind the project

The story behind the project: ALENTAR-J-CM was created as an institutional collaborative project with a common vision: to combat emotional distress among young people through research and the application of advanced technologies in mental health.

Meet the team

RESULTS

Real-world application in the social and healthcare system

We transfer the research and technology developed in ALENTAR-J-CM to create real solutions that improve care and prevention in youth mental health.

Find out how

Early detection

Identification and definition of paralinguistic and speech-related parameters.

Real-World validation

Validation of the obtained parameters in real-world contexts.

Analysis

Written and vocal expression data collection and analysis from diverse populations.

Solution development

Development of evidence-based prevention resources and services.

RESULTS

Real-world application in the social and healthcare system

We transfer the research and technology developed in ALENTAR-J-CM to create real solutions that improve care and prevention in youth mental health.

Early detection

Identification and definition of paralinguistic and speech-related parameters.

Real-World validation

Validation of the obtained parameters in real-world contexts.

Analysis

Written and vocal expression data collection and analysis from diverse populations.

Solution development

Development of evidence-based prevention resources and services.

find out how

Publications

Mental health literacy in children and adolescents in low- and middle-income countries

June 1, 2026

Globally, mental illnesses are the primary cause of disease burden among children and young people (CYP). This issue disproportionately affects…

Can Large Language Models (LLMs) and text-embedding models detect depression and suicide risk based on Sentence Completion Test (SCT) narratives of psychiatric patients?

May 11, 2026

Mental health assessment still relies heavily on clinical interviews and subjective judgment. With the recent development of LLMs, researchers are…

Hypomentalizing and suicide reattempt: what does the evidence show?

April 27, 2026

Suicidal behaviour is a complex and multifaceted phenomen in which several biological, psychological, clinical, and sociocultural aspects are intertwined. Hypomentalizing,…

GET INVOLVED

Every step matters.

Let’s join efforts to support emotional well-being in our society.

Contact

This website is supported by the Dirección General de Investigación e Innovación Tecnológica de la Comunidad de Madrid (Orden 3177/2024) through the I+D Technological activities program (TEC-2024/COM-224) and the European Regional Development Fund (ERDF)

ALENTAR-J-CM Project

ALENTAR-J-CMProject

Research partners

Collaborating partners

The story behind the project

Real-world application in the social and healthcare system

Early detection

Real-World validation

Analysis

Solution development

Real-world application in the social and healthcare system

Early detection

Real-World validation

Analysis

Solution development

Publications

Mental health literacy in children and adolescents in low- and middle-income countries

Can Large Language Models (LLMs) and text-embedding models detect depression and suicide risk based on Sentence Completion Test (SCT) narratives of psychiatric patients?

Hypomentalizing and suicide reattempt: what does the evidence show?

Every step matters.

ALENTAR-J-CM
Project