Guide-yakabatana mibvunzo · Pakati Nhanho

AI muNutrition uye Dietetics Quiz

Ongorora kucherechedzwa kwechikafu kweAI, fungidziro yechikamu, dhatabhesi rezvikafu, mhinduro yega yega glucose, kuongororwa kwekiriniki, uye zvipingamupinyi zvekudya.

Nzira dzekutungamira dzinoenderanaAI Mukudya uye Dietetics
Mubvunzo 1 ye 8

Ndeipi tekinoroji inobvumira maapplication ekutema chikafu kufungidzira macalorie kubva pamufananidzo wekudya?

Tarisa mubvunzo wese8 mibvunzo

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

  1. Ndeipi tekinoroji inobvumira maapplication ekutema chikafu kufungidzira macalorie kubva pamufananidzo wekudya?
    • Kuona komputa ine neural network
    • Blockchain mabhuku
    • Radio-frequency identification
    • Manual barcode yekupinda chete
  2. Chinhu chakakosha chekuwana kubva mukuenderera mberi kweglucose monitor research ndechekuti:
    • Munhu wose anopindura zvakafanana kune zvokudya zvakafanana
    • Vanhu vanogona kuva nemhinduro dzakasiyana-siyana dzeshuga yeropa pakudya kumwe chete
    • Mhinduro yeglucose yakafanana zvisinei nenguva yekudya
    • Chikafu hachina kuyerwa mhedzisiro paglucose
  3. How can an EHR-based machine-learning model support malnutrition screening?
    • Kutsiva vese vekudya kwevanhu
    • Kubika chikafu chevarwere zvoga
    • Flag patients whose records suggest elevated malnutrition risk for dietitian review
    • Kuseta tembiricha dzemuchipatara
  4. Nderipi dhatabhesi rinowanzoshandiswa kushandura zvikafu zvinozivikanwa kuita zvinovaka muviri?
    • Iyo Dewey Decimal System
    • The periodic table
    • Indekisi yemusika wemasheya
    • USDA FoodData Central
  5. Ndeipi yekuisa inonyanya kunatsiridza AI kufanotaura kwemunhu glycemic mhinduro?
    • Inoenderera mberi glucose yekutarisa uye microbiome data
    • Munhu anofarira ruvara
    • Kupenya kwescreen yefoni
    • Kufembera kwemamiriro ekunze
  6. What limitation has research on LLM-generated nutrition plans highlighted?
    • Havagone kuburitsa chero chinyorwa
    • Plans may be inaccurate or inconsistent with clinical nutrition guidelines
    • Vanongoshanda pasina Indaneti
    • Vanoda kunyorerwa
  7. What visual cue can help an image-based diet system estimate food volume?
    • The phone’s battery level
    • The color of the plate alone
    • A known-size reference object in the image, such as a cup or spoon
    • The restaurant’s opening hours
  8. What dietary factors may a meal-planning tool need to account for in a renal diet?
    • Only the food’s packaging color
    • A fixed calorie limit for every patient
    • The meal’s social-media popularity
    • Nutrient limits such as potassium and phosphorus, along with carbohydrate constraints when relevant