{"id":6648,"date":"2023-10-21T19:52:58","date_gmt":"2023-10-21T19:52:58","guid":{"rendered":"https:\/\/dailyai.com\/?p=6648"},"modified":"2023-10-21T20:03:47","modified_gmt":"2023-10-21T20:03:47","slug":"researchers-diagnose-diabetes-in-seconds-using-voice-recordings","status":"publish","type":"post","link":"https:\/\/dailyai.com\/sv\/2023\/10\/researchers-diagnose-diabetes-in-seconds-using-voice-recordings\/","title":{"rendered":"Forskare diagnostiserar diabetes p\u00e5 n\u00e5gra sekunder med hj\u00e4lp av r\u00f6stinspelningar"},"content":{"rendered":"

Forskare vid v\u00e5rdforskningsf\u00f6retaget Klick Labs har utvecklat en maskininl\u00e4rningsmodell som kan fastst\u00e4lla f\u00f6rekomsten av typ 2-diabetes fr\u00e5n en kort r\u00f6stinspelning p\u00e5 bara 6 till 10 sekunder.\u00a0<\/b><\/p>\n

Modellen visar en maximal testprecision p\u00e5 89% f\u00f6r kvinnor och 86% f\u00f6r m\u00e4n n\u00e4r den kombineras med andra m\u00e4tv\u00e4rden som BMI (Body Mass Index).\u00a0<\/span><\/p>\n

\"V\u00e5r forskning visar p\u00e5 betydande r\u00f6stvariationer mellan individer med och utan typ 2-diabetes och kan f\u00f6r\u00e4ndra hur man inom sjukv\u00e5rden screenar f\u00f6r diabetes\", s\u00e4ger Jaycee Kaufman, forskare p\u00e5 Klick Labs.<\/span><\/p>\n

Metoden, <\/span>publicerad i Mayo Clinic Proceedings<\/span><\/a>, kr\u00e4ver ett kort ljudklipp inspelat med smartphone.\u00a0\u00a0<\/span><\/p>\n

\"De nuvarande metoderna f\u00f6r att uppt\u00e4cka brott kan kr\u00e4va mycket tid, resor och kostnader. R\u00f6sttekniken har potential att helt undanr\u00f6ja dessa hinder\", s\u00e4ger Kaufman.<\/span><\/p>\n

I studien analyserades 18.000 inspelningar i syfte att identifiera unika akustiska egenskaper som skiljer diabetiker fr\u00e5n icke-diabetiker genom att uppt\u00e4cka subtila skillnader i tonh\u00f6jd och intensitet som \u00e4r om\u00e4rkliga f\u00f6r det m\u00e4nskliga \u00f6rat.<\/span><\/p>\n

Senare eller l\u00e5ngt framskriden diabetes kan p\u00e5verka r\u00f6sten genom att orsaka nervskador och f\u00f6rs\u00e4mra blodfl\u00f6det, vilket leder till tillst\u00e5nd som neuropati som p\u00e5verkar st\u00e4mbanden. Detta kan leda till en svag, hes eller tr\u00f6tt klingande r\u00f6st.\u00a0<\/span><\/p>\n

Dessutom kan diabetes leda till muntorrhet p\u00e5 grund av minskad salivproduktion, vilket ytterligare bidrar till r\u00f6stproblem.\u00a0<\/span><\/p>\n

Forskarna betonar AI:s v\u00e4xande roll inom sjukv\u00e5rden och tror att denna r\u00f6stteknik kan utvidgas till att diagnostisera andra h\u00e4lsotillst\u00e5nd.<\/span><\/p>\n

Yan Fossat, Vice President p\u00e5 Klick Labs, s\u00e4ger: \"V\u00e5r forskning understryker den enorma potential som r\u00f6stteknologi har f\u00f6r att identifiera typ 2-diabetes och andra h\u00e4lsotillst\u00e5nd. R\u00f6stteknologi kan revolutionera sjukv\u00e5rden som ett tillg\u00e4ngligt och prisv\u00e4rt digitalt screeningverktyg.\"<\/span><\/p>\n

Mer om studien<\/span><\/h2>\n

Det h\u00e4r \u00e4r en fascinerande studie, men \u00e4r den metodologiskt robust? <\/span><\/p>\n

Urvalet \u00e4r relativt litet och det finns begr\u00e4nsad information om hur l\u00e5ngt framskriden diabetes \u00e4r i diabetikergruppen och lite information om kontrollgruppen.<\/span><\/p>\n

Att f\u00f6ruts\u00e4ga de subtila tonala egenskaperna i tal hos diabetiker verkar dock vara m\u00f6jligt f\u00f6r dem som har en avancerad eller okontrollerad form av sjukdomen.\u00a0<\/span><\/p>\n

H\u00e4r \u00e4r en n\u00e4rmare titt:<\/span><\/p>\n

    \n
  1. M\u00e5ls\u00e4ttning:<\/b> Studien syftar till att unders\u00f6ka om r\u00f6stanalys kan bidra till f\u00f6runders\u00f6kning eller \u00f6vervakning av diabetes mellitus typ 2 (T2DM). Forskarna fokuserade p\u00e5 att identifiera skillnader i r\u00f6stinspelningar mellan personer med och utan T2DM.<\/span><\/li>\n
  2. Metodik:<\/b> 267 deltagare, b\u00e5de m\u00e4n och kvinnor, inklusive personer utan diabetes och T2DM, spelade in en fast fras flera g\u00e5nger dagligen under tv\u00e5 veckor med hj\u00e4lp av en smartphone-app. Denna process genererade \u00f6ver 18.000 inspelningar. Teamet extraherade 14 olika akustiska funktioner fr\u00e5n dessa inspelningar f\u00f6r att analysera och j\u00e4mf\u00f6ra r\u00f6sterna hos deltagare med diabetes och T2DM.<\/span><\/li>\n
  3. Resultat:<\/b> Forskarna uppt\u00e4ckte betydande skillnader i r\u00f6stinspelningarna fr\u00e5n b\u00e5de m\u00e4n och kvinnor n\u00e4r de j\u00e4mf\u00f6rde deltagare som inte hade diabetes med deltagare som hade diabetes mellitus. De identifierade specifika r\u00f6stkarakt\u00e4ristika som p\u00e5 ett korrekt s\u00e4tt f\u00f6rutsp\u00e5dde T2DM-status, s\u00e4rskilt n\u00e4r de kombinerades med uppgifter om \u00e5lder och BMI. Den maximala testnoggrannheten uppgick till 89% f\u00f6r kvinnor och 86% f\u00f6r m\u00e4n.\u00a0<\/span><\/li>\n
  4. Konsekvenser:<\/b> Dessa resultat tyder p\u00e5 att r\u00f6stanalys har potential som ett verktyg f\u00f6r f\u00f6runders\u00f6kning eller \u00f6vervakning av T2DM. Denna metod kan vara s\u00e4rskilt anv\u00e4ndbar i avl\u00e4gsna samh\u00e4llen och erbjuda ett tillg\u00e4ngligt och icke-invasivt alternativ f\u00f6r tidig uppt\u00e4ckt och l\u00f6pande \u00f6vervakning.<\/span><\/li>\n<\/ol>\n

    Tanken p\u00e5 att diagnostisera sjukdomar med hj\u00e4lp av en r\u00f6stinspelning kan verka l\u00e5ngs\u00f6kt, och det \u00e4r viktigt att inse att de b\u00e4sta resultaten endast uppn\u00e5ddes n\u00e4r inspelningarna kombinerades med BMI. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Forskare vid v\u00e5rdforskningsf\u00f6retaget Klick Labs har utvecklat en maskininl\u00e4rningsmodell som kan fastst\u00e4lla f\u00f6rekomsten av typ 2-diabetes fr\u00e5n en kort r\u00f6stinspelning p\u00e5 bara 6 till 10 sekunder. Modellen visar en maximal testnoggrannhet p\u00e5 89% f\u00f6r kvinnor och 86% f\u00f6r m\u00e4n n\u00e4r den kombineras med andra m\u00e4tv\u00e4rden som kroppsmasseindex (BMI). \"V\u00e5r forskning belyser betydande r\u00f6stvariationer mellan individer med och utan typ 2-diabetes och kan f\u00f6r\u00e4ndra hur det medicinska samfundet screenar f\u00f6r diabetes\", kommenterade Jaycee Kaufman, forskare vid Klick Labs. Metoden, som publicerades i Mayo Clinic Proceedings, kr\u00e4ver<\/p>","protected":false},"author":2,"featured_media":6649,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[203,105,101],"class_list":["post-6648","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biotech","tag-machine-learning","tag-medtech"],"yoast_head":"\nResearchers diagnose diabetes in seconds using voice recordings | DailyAI<\/title>\n<meta name=\"description\" content=\"Researchers at healthcare research company Klick Labs have developed a machine learning model that can determine the presence of Type 2 diabetes from a brief voice recording of just 6 to 10 seconds.\u00a0\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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