98510e9d40ae33fa70eb · Comparison of Artificial Intelligence based approaches to cell function prediction

{
  "title_en": "Comparison of Artificial Intelligence based approaches to cell function prediction",
  "designation": "",
  "series": "",
  "status": "",
  "date": "2019-07-11",
  "date_original": "July 11, 2019",
  "url": "https://www.nist.gov/publications/comparison-artificial-intelligence-based-approaches-cell-function-prediction",
  "source": "NIST Publications",
  "display_en": "",
  "authors_en": "Sarala Padi , Petru S. Manescu , Nicholas Schaub, Nathan Hotaling, Carl G. Simon Jr. , Peter Bajcsy",
  "abstract_excerpt_en": "Predicting Retinal Pigment Epithelium (RPE) cell functions in stem cell implants using non-invasive bright field microscopy imaging is a critical task for clinical deployment of stem cell therapies. Such cell function predictions can be carried out either",
  "id": "98510e9d40ae33fa70eb",
  "sources": [
    "NIST Publications"
  ],
  "source_records": [
    {
      "title_en": "Comparison of Artificial Intelligence based approaches to cell function prediction",
      "designation": "",
      "series": "",
      "status": "",
      "date": "2019-07-11",
      "date_original": "July 11, 2019",
      "url": "https://www.nist.gov/publications/comparison-artificial-intelligence-based-approaches-cell-function-prediction",
      "source": "NIST Publications",
      "display_en": "",
      "authors_en": "Sarala Padi , Petru S. Manescu , Nicholas Schaub, Nathan Hotaling, Carl G. Simon Jr. , Peter Bajcsy",
      "abstract_excerpt_en": "Predicting Retinal Pigment Epithelium (RPE) cell functions in stem cell implants using non-invasive bright field microscopy imaging is a critical task for clinical deployment of stem cell therapies. Such cell function predictions can be carried out either"
    }
  ],
  "translation_state": "none"
}