No abstract

No abstract

Background Adequate cytology is limited by insufficient cytologists in a large‐scale cervical cancer screening. We aimed to develop an artificial intelligence (AI)‐assisted cytology system in cervical cancer screening program. Methods We conducted a perspective cohort study within a population‐based cervical cancer screening program for 0.7 million women, using a validated AI‐assisted cytology system. For comparison, cytologists examined all slides classified by AI as abnormal and a randomly selected 10% of normal slides. Each woman with slides classified as abnormal by either AI‐assisted or manual reading was diagnosed by colposcopy and biopsy. The outcomes were histologically confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+). Results Finally, we recruited 703 103 women, of whom 98 549 were independently screened by AI and manual reading. The overall agreement rate between AI and manual reading was 94.7% (95% confidential interval [CI], 94.5%‐94.8%), and kappa was 0.92 (0.91‐0.92). The detection rates of CIN2+ increased with the severity of cytology abnormality performed by both AI and manual reading (Ptrend < 0.001). General estimated equations showed that detection of CIN2+ among women with ASC‐H or HSIL by AI were significantly higher than corresponding groups classified by cytologists (for ASC‐H: odds ratio [OR] = 1.22, 95%CI 1.11‐1.34, P < .001; for HSIL: OR = 1.41, 1.28‐1.55, P < .001). AI‐assisted cytology was 5.8% (3.0%‐8.6%) more sensitive for detection of CIN2+ than manual reading with a slight reduction in specificity. Conclusions AI‐assisted cytology system could exclude most of normal cytology, and improve sensitivity with clinically equivalent specificity for detection of CIN2+ compared with manual cytology reading. Overall, the results support AI‐based cytology system for the primary cervical cancer screening in large‐scale population.

For the preparation of lightweight and high-performance electromagnetic interference shielding material, the poor dispersion of carbon nanotubes (CNTs) and weak interfacial strength degrade the mechanical properties of the polymer-based composite with extremely high filler contents. Herein cellulose nanofibers (CNFs) prepared by TEMPO-mediated oxidation exhibits a dispersive action for multiwalled carbon nanotube (MWCNTs) without chemical functionalization of the MWCNTs or the use of surfactant. Thus a robust and flexible CNF/MWCNT composite film can be fabricated by simple vacuum filtration and hot-pressing method. This composite film (thickness 0.15 mm) shows an electromagnetic interference shielding effectiveness (EMI SE) of 45.8 dB in the X-band. Thanks to the all-fiber structure and the association between CNFs and MWCNTs, it exhibits good flexibility and tensile strength up to 48 MPa, which is superior to other reported MWCNT-based films for electromagnetic shielding, giving it the potential to be used in flexible electronics and wearable devices.

No abstract