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Using Voice AI to Detect Mental Health Disorders - David Liu

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Manage episode 437968977 series 3506752
Conteúdo fornecido por Dave Anderson. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Dave Anderson ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

In this podcast episode Dave Anderson is joined by David Lowe, the CEO of Sonde Health, a company that has developed an AI technology to detect early indications of mental health disorders through analyzing the sound of a person's voice. The conversation explores the potential benefits of using voice AI to identify symptoms of depression, anxiety, and cognitive impairment. They discuss the importance of early detection and intervention, the privacy concerns surrounding voice data, and the goal of improving mental health and productivity in the workplace. The episode highlights the need for increased awareness and understanding of mental health and the potential of AI technology in this field.

Takeaways

  • Voice AI technology can analyze the sound of a person's voice to detect early indications of mental health disorders.
  • Early detection and intervention can lead to better outcomes and improved mental health.
  • Privacy concerns surrounding voice data need to be addressed and transparency is crucial.
  • Improving mental health can have a positive impact on workplace productivity.

Sound Bites

  • "What if a voice technology could work out whether or not someone had early indication of anxiety, depression, or some form of mental stress? Would you want to know?"
  • "We are able to measure the biomarkers, these signals that are coming from a specific data source. And in this case, it's your voice."
  • "No machine can tell you that. You need clinicians. In fact, you need several clinicians to be able to make that determination over time."

  continue reading

33 episódios

Artwork
iconCompartilhar
 
Manage episode 437968977 series 3506752
Conteúdo fornecido por Dave Anderson. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Dave Anderson ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

In this podcast episode Dave Anderson is joined by David Lowe, the CEO of Sonde Health, a company that has developed an AI technology to detect early indications of mental health disorders through analyzing the sound of a person's voice. The conversation explores the potential benefits of using voice AI to identify symptoms of depression, anxiety, and cognitive impairment. They discuss the importance of early detection and intervention, the privacy concerns surrounding voice data, and the goal of improving mental health and productivity in the workplace. The episode highlights the need for increased awareness and understanding of mental health and the potential of AI technology in this field.

Takeaways

  • Voice AI technology can analyze the sound of a person's voice to detect early indications of mental health disorders.
  • Early detection and intervention can lead to better outcomes and improved mental health.
  • Privacy concerns surrounding voice data need to be addressed and transparency is crucial.
  • Improving mental health can have a positive impact on workplace productivity.

Sound Bites

  • "What if a voice technology could work out whether or not someone had early indication of anxiety, depression, or some form of mental stress? Would you want to know?"
  • "We are able to measure the biomarkers, these signals that are coming from a specific data source. And in this case, it's your voice."
  • "No machine can tell you that. You need clinicians. In fact, you need several clinicians to be able to make that determination over time."

  continue reading

33 episódios

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