The researchers created a digital model of psychology aimed to improve mental health. The system offers superior personalization and identifies the shortest path toward a cluster of mental stability for any individual.
Deep Longevity, in collaboration with Harvard Medical School, presents a deep learning approach to mental health.
Deep Longevity has published a paper in Aging-US outlining a machine learning approach to human psychology in collaboration with Nancy Etcoff, Ph.D., Harvard Medical School, an authority on happiness and beauty.
The authors created two digital models of human psychology based on data from the Midlife in the United States study.
The first model is an ensemble of deep neural networks that predicts respondents’ chronological age and psychological well-being in 10 years using information from a psychological survey. This model depicts the trajectories of the human mind as it ages.
Deep Longevity has published a paper in Aging-US outlining a machine learning approach to human psychology in collaboration with Nancy Etcoff, Ph.D., Harvard Medical School, an authority on happiness and beauty.
The authors created two digital models of human psychology based on data from the Midlife in the United States study.
The first model is an ensemble of deep neural networks that predicts respondents’ chronological age and psychological well-being in 10 years using information from a psychological survey. This model depicts the trajectories of the human mind as it ages.
It also demonstrates that the capacity to form meaningful connections, as well as mental autonomy and environmental mastery, develops with age. It also suggests that the emphasis on personal progress is constantly declining, but the sense of having a purpose in life only fades after 40-50 years.
These results add to the growing body of knowledge on socioemotional selectivity and hedonic adaptation in the context of adult personality development. READ MORE...
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