AIMC Topic: Fallopian Tube Neoplasms

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Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone.

Scientific reports Sep 27, 2021
High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-year survival of less than 50%. Beyond determining and confirming the diagnosis itself, pathologist ...
Humans Neural Networks, Computer Artificial Intelligence Retrospective Studies Female Aged Adult Middle Aged Treatment Outcome Ovarian Neoplasms Peritoneal Neoplasms Chemotherapy, Adjuvant Cystadenocarcinoma, Serous Platinum Compounds Fallopian Tube Neoplasms
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Assessing the impact of deep-learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes.

The journal of pathology. Clinical research Nov 1, 2024
In recent years, it has become clear that artificial intelligence (AI) models can achieve high accuracy in specific pathology-related tasks. An example is our deep-learning model, designed to automatically detect serous tubal intraepithelial carcinom...
Humans Female Reproducibility of Results Deep Learning Image Interpretation, Computer-Assisted Observer Variation Cystadenocarcinoma, Serous Carcinoma in Situ Fallopian Tube Neoplasms
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