Makale detayı · 2022
Deep Learning-Enabled Technologies for Bioimage Analysis
- Yıl
- 2022
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı MICROMACHINES
- Katalog eşleşmesi (ISSN) Micromachines
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.
Konular
Atıflar
OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.
21 atıf
OpenAlex cited_by_count (önbellek / veritabanı)
Yerel katalogda bu makaleye atıf yapan 8 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
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