[Deep learning algorithm] assisted detection of nasopharyngeal carcinoma on endoscopic images: a national, multicentre, model development and validation study
NOTE: The original title was "Artificial intelligence-assisted detection[...]", so I modified it to be more specific.
Background:Nasopharyngeal carcinoma is highly curable when diagnosed early. However, the nasopharynx’s obscure anatomical position and the similarity of local imaging manifestations with those of other nasopharyngeal diseases often lead to diagnostic challenges, resulting in delayed or missed diagnoses. Our aim was to develop a deep learning algorithm to enhance an otolaryngologist’s diagnostic capabilities by differentiating between nasopharyngeal carcinoma, benign hyperplasia, and normal nasopharynx during endoscopic examination.
Findings
Endoscopic images used in the internal study (Jan 1, 2017, to Jan 31, 2023) were from 15 521 individuals (9033 [58·2%] men and 6488 [41·8%] women; mean age 47·6 years [IQR 38·4–56·8]). Images from 945 participants (538 [56·9%] men and 407 [43·1%] women; mean age 45·2 years [IQR 35·2– 55·2]) were used in the external validation. STND in the internal dataset discriminated normal nasopharynx images from abnormalities (benign hyperplasia and nasopharyngeal carcinoma) with an area under the curve (AUC) of 0·99 (95% CI 0·99–0·99) and malignant images (ie, nasopharyngeal carcinoma) from non-malignant images (ie, benign hyperplasia and normal nasopharynx) with an AUC of 0·99 (95% CI 0·98–0·99). In the external validation, the system had an AUC for the detection of nasopharyngeal carcinoma of 0·95 (95% CI 0·94–0·96), a sensitivity of 91·6% (95% CI 89·3–93·5), and a specificity of 86·1% (95% CI 84·1–87·9). In the multireader, multicase study, the artificial intelligence (AI)-assisted strategy enhanced otolaryngologists’ diagnostic accuracy by 7·9%, increasing from 83·4% (95% CI 80·1–86·7, without AI assistance) to 91·2% (95% CI 88·6–93·9, with AI assistance; p<0·0001) for primary care otolaryngologists. Reading time per image decreased with the aid of the AI model (mean 5·0 s [SD 2·5] vs 6·7 s [6·0] without the model; p=0·034).
(emphasis mine)
InterpretationOur deep learning system has shown significant clinical potential for the practical application of nasopharyngeal carcinoma diagnosis through endoscopic images in real-world settings. The system offers substantial benefits for adoption in primary hospitals, aiming to enhance specificity, avoid additional biopsies, and reduce missed diagnoses.
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(25)00041-X/fulltext
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ChunkMcHorkle
in reply to Wispy2891 • • •Use the offline installer, which is for offline and airgapped machines. It turns off the AI prompt builder as well as all the telemetry shite:
support.logi.com/hc/en-us/arti…
Logitech Options+ offline installer
Logitech Support + Downloadbluesheep
in reply to ChunkMcHorkle • • •ChunkMcHorkle
in reply to bluesheep • • •