The authors studied the role of 70-Kd heat shock protein (HSP70) in the progression of breast cancer by examining the correlation between the expression of HSP70 and epidermal growth factor receptor, c-erbB-2, p53, and estrogen receptor in 124 cases of invasive primary human breast cancers. Positivity of an anti-HSP70 monoclonal antibody, C92, was closely associated with the elevation of estrogen receptor (P < .008), whereas it inversely correlated with the expression of p53 (P < .01). In addition, the expression of HSP70 correlated inversely with the expression of epidermal growth factor receptor, although the correlation was not statistically significant (P = .06). These results suggest that the expression of HSP70 plays a role in the progression of human breast cancer.
Background
There are no published reports evaluating the ability of artificial intelligence (AI) in the endoscopic diagnosis of superficial laryngopharyngeal cancer (SLPC). We presented our newly developed diagnostic AI model for SLPC detection.
Methods
We used RetinaNet for object detection. SLPC and normal laryngopharyngeal mucosal images obtained from narrow‐band imaging were used for the learning and validation data sets. Each independent data set comprised 400 SLPC and 800 normal mucosal images. The diagnostic AI model was constructed stage‐wise and evaluated at each learning stage using validation data sets.
Results
In the validation data sets (100 SLPC cases), the median tumor size was 13.2 mm; flat/elevated/depressed types were found in 77/21/2 cases. Sensitivity, specificity, and accuracy improved each time a learning image was added and were 95.5%, 98.4%, and 97.3%, respectively, after learning all SLPC and normal mucosal images.
Conclusions
The novel AI model is helpful for detection of laryngopharyngeal cancer at an early stage.
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