How Sleep Sounds & AI Detect Sickness Days Early

{
  "id": "PP1162416",
  "track": "Health",
  "focus_area": null,
  "category": "Presentation",
  "event_id": "PP1162416",
  "event_type": "panel",
  "format": "Presentation",
  "genre": null,
  "subgenre": null,
  "name": "How Sleep Sounds & AI Detect Sickness Days Early",
  "presented_by": null,
  "publish_at": "2025-11-03T16:30:00.000-06:00",
  "reservable": true,
  "reservable_id": "PP1162416",
  "reserved": false,
  "date": "2026-03-18",
  "end_time": "2026-03-18T14:00:00.000-05:00",
  "start_time": "2026-03-18T13:00:00.000-05:00",
  "message": null,
  "image": null,
  "credentials": [
    {
      "name": "Platinum Badge",
      "type": "platinum"
    },
    {
      "name": "Innovation Badge",
      "type": "innovation"
    }
  ],
  "contributors": [
    {
      "id": 77966,
      "company": "Sleep Cycle",
      "credential_types": [
        "innovation"
      ],
      "entity_id": 2238918,
      "name": "Mikael Kågebäck",
      "speaker_types": [],
      "title": "Chief Technology Officer",
      "image": {
        "alt_text": "Mikael Kågebäck",
        "credit": null,
        "url": "https://images.sxsw.com/pNFI8IoDMxs0-hHMC8maJNJJRyA=/600x600/images.sxsw.com/48/06e3bbaf-8d57-01f2-37b1-50f9d6e6b010/pcid-1622911"
      },
      "speaker_type": "Speaker",
      "details": "Mikael Kågebäck, Chief Technology Officer at Sleep Cycle, holds a Ph.D. in AI and Machine Learning from Chalmers University of Technology, Gothenburg. Steering Sleep Cycle's technical direction, he spearheads essential machine learning research, leveraging his extensive background in tech, AI and ML, with a particular focus on deep neural networks. Bringing diverse experience as a seasoned system architect and software engineer, Mikael actively drives Sleep Cycle's technological innovation, shaping the future of sleep technology.",
      "links": {},
      "type": "person"
    }
  ],
  "venue": {
    "accessible": false,
    "age_policy": null,
    "floor": "3",
    "id": "V0453",
    "indoor_outdoor": "INDOOR",
    "name": "Salon C",
    "parent_id": "V0403",
    "parent_venue_name": "JW Marriott",
    "venue_entry_info": null,
    "formats": null,
    "location": {
      "address": "110 E 2nd St.",
      "lat_lon": [
        30.2645713,
        -97.743198
      ],
      "city": "Austin",
      "postal_code": "78701",
      "state": "TX",
      "name": "JW Marriott"
    },
    "root": {
      "accessible": null,
      "age_policy": null,
      "floor": null,
      "id": "V0403",
      "indoor_outdoor": null,
      "name": "JW Marriott",
      "parent_id": null,
      "parent_venue_name": null,
      "venue_entry_info": null,
      "formats": null
    },
    "events": "[omitted 5 venue events]"
  },
  "description": "What if your breathing patterns could warn you that you are getting sick days before you have noticeable respiratory illness symptoms? The answer lies in sleep audio analysis powered by AI. This session explores how new advances can help us detect patterns far before our bodies notice. Sound is passive, honest, and scalable, and with AI trained on 3B nights of data, it can turn every bedroom into a node in an early-warning health network. AI has the power to turn sleep audio into a new public health infrastructure: one that listens, learns, and helps us act before symptoms even appear.",
  "experience_level": "Beginner",
  "accessibility": [
    "Closed captioned"
  ],
  "accessible_venue": false,
  "add_bcl_url": false,
  "add_slido": false,
  "age_policy": null,
  "american_sign_language": false,
  "apple_url": null,
  "audio_description": false,
  "caption_url": null,
  "closed_captioned": true,
  "cpe_credit": false,
  "has_subtitles": false,
  "hash_tags": [],
  "high_sensory_experience": false,
  "live": false,
  "long_description": "What if your breathing patterns could warn you that you are getting sick days before you have noticeable respiratory illness symptoms? The answer lies in sleep audio analysis powered by AI. This session explores how new advances can help us detect patterns far before our bodies notice. Sound is passive, honest, and scalable, and with AI trained on 3B nights of data, it can turn every bedroom into a node in an early-warning health network. AI has the power to turn sleep audio into a new public health infrastructure: one that listens, learns, and helps us act before symptoms even appear.",
  "meeting_url": null,
  "meeting_url_live": false,
  "mentorly_url": null,
  "mobile_audio_url": null,
  "open_captioned": false,
  "playlist_tag": null,
  "rebroadcast": false,
  "recommended_ids": [],
  "search_conversions": null,
  "short_program": false,
  "slido_url": null,
  "sort": "HOW SLEEP SOUNDS & AI DETECT SICKNESS DAYS EARLY",
  "source": "Official",
  "squad_up_url": null,
  "stream_embed": null,
  "stream_id": null,
  "stream_url": null,
  "strobe_warning": false,
  "subdiscipline": null,
  "summit": null,
  "summit_display_name": null,
  "tags": [
    {
      "id": 951,
      "name": "Science",
      "created_at": "2016-11-04T11:44:17.754-05:00",
      "updated_at": "2024-01-25T14:52:52.593-06:00",
      "sort": "SCIENCE",
      "alpha": "S"
    }
  ],
  "talent_attending": null,
  "title_only": false,
  "track_display_name": "Health track sponsored by Eli Lilly",
  "trailer_id": null,
  "trailer_url": null,
  "video_on_demand": null,
  "vimeo_id": null,
  "vod": false,
  "xr_project_type": null,
  "youtube_id": null,
  "related_sales_client": null
}